Have you recently successfully defended your doctorate degree in engineering or science? Do you wish to expand your career opportunities by doing a post doctorate?

Available Jobs

MSCA-PF 2021 CALL: Nanoplasmonic detection of extracellular vesicles in plasma for early diagnosis of stroke.

Mol
Postdoc
Description: 

Context and research challenge

Stroke is a major cause of death and disability worldwide. Early diagnosis of stroke and treatment initiation is of major importance for patient outcome, but rapid point of care blood tests are lacking.  Extracellular vesicles (EVs) derived from several cell types of the brain and circulation have been shown to be released into the blood in the acute phase of a stroke event and correlate with the pathophysiology[1]. These hold promise as new biomarker source for acute stroke diagnostics. 
The detection of specific EV subsets in blood plasma is challenging due to their small size, low numbers, low abundance of surface biomarkers, and the presence of other biomolecules with similar properties (size, density, refractive index). This can be overcome by affinity-based methods that target disease-specific EV membrane proteins, thus providing information about rare sub-populations of EVs. Nanoparticles, when surface conjugated with affinity binding ligands, have the potential to enable EV purification from complex biofluids and boost sensitivity of their detection due to their unique physical properties. 

Based on a nanoplasmonic biosensor platform for lectin detection in stroke, developed in the H2020 MSCA-ITN NanoCarb project[2], the goal of this project is to redesign the nanogold-based platform for sensitive detection of plasma-derived EVs for acute stroke diagnostics.

Approach

Gold nanoparticles will be conjugated with antibodies and/or alternative affinity ligands (e.g. glycans, nanobodies), characterized, and used to assess their binding of selected EV biomarkers (e.g. ICAM-1/CD54, CD62E) using localised surface plasmon resonance (LSPR) detection and biolayer interferometry. The nanogold-bioconjugates and binding protocols will be optimized using EV isolates in buffer, and the performance of EV detection (sensitivity, specificity, dynamic range, reproducibility) determined. Next, the bioassay will be further developed to allow direct binding and detection of DRS-specific EV subsets in plasma samples. 

The research project combines multidisciplinary fields of research in physics, biomaterial science, surface chemistry and clinical diagnostics.

[1] Stenz KT, Just J, Blauenfeldt RA, Drasbek KR. Extracellular vesicles in acute stroke diagnostics. Biomedicines 2020, 8, 248.
[2] Pancaro A, Szymonik M, Georgiou PG, Baker AN, Walker M, Adriaensens P, Hendrix J, Gibson MI, Nelissen I. The Nature of Polymeric Glyco-Linker Controls the Signal Outputs for Plasmonic Gold Nanorods Biosensors in Complex Media due to Biocorona Formation. Submitted for publication.

With this call, we invite researchers to submit their resumé (including track-record) and a one-page project description, that will be the basis for selecting candidates with whom we will collaborate for developing a competitive MSCA-PF proposal.

Collaborations

Collaboration with academic and/or clinical partner is planned who bring in their expertise in ischemic stroke and access to clinical samples.

Deadline application to VITO

Interested candidates should submit their resume (incl. track record) and a one-page note describing the project for which a Marie Curie grant will be applied, as soon as possible and no later than Friday 30 April 2021 17h Brussels time.

Supervisor

Successful candidates will be supervised by Dr. Inge Nelissen, Team leader Nanobiotechnology. 

contact: inge.nelissen@vito.be

Deadline MSCA-PF 2021

Wednesday 15 September 2021 17h Brussels time. 

Target start date

The EU informs the results on the MSCA-PF applications in February 2022. Successful candidates are expected to be available to start within the following two months and no later than summer 2022.

POSTDOC Sustainable bio-based polymer materials using lignin-first biorefining

Mol
Postdoc
Description: 

Scion (New Zealand) and VITO (Belgium) are seeking a skilled and enthusiastic chemist to investigate the synthesis and performance of novel thermoplastic and thermoset bio-based polymers derived from depolymerised lignins. The project will involve aspects of depolymerising lignin to platform chemicals, synthesis and characterisation of novel bio-based polymers, and material property and applications testing. A successful candidate will have a PhD and research experience in polymer and/or organic chemistry with a track record of publication in international journals. 

The Postdoctoral fellow will undertake research work at Scion and VITO supported by a team with expertise in lignin chemistry, polymer chemistry and formulation, and materials science. This unique opportunity will provide you with internationally recognised skills and knowledge in the field of sustainable chemistry and processing for value-added biomaterials that will advance your research career. 

Scion, a New Zealand Crown Research Institute, is committed to enhancing the environmental and economic transformation of New Zealand, working toward a more sustainable, bio-based future. With more than 60 years of heritage in forestry science, Scion today demonstrates national leadership, world-class innovation and excellence in research and development. Scion’s head office is located in Rotorua, at the edge of the world-famous Whakarewarewa Forest. This location is close to lakes, forests, geothermal areas, beaches and volcanic ski-fields making it a great working environment with many opportunities to balance work with other things that are important in life. 

VITO, the Flemish Institute for Technological Research (www.vito.be), is an independent research organisation with a staff of approximately 760 employees. It implements customer-oriented research and develops innovative products and processes for both the public and private sector in the areas of chemistry, materials, environment, energy and health. The multidisciplinary skills and technological know-how of VITO’s employees make this organisation a crossroads of research & development, where state-of-the-art technologies are successfully blended into practical applications. 

This is a full-time position for two years, available as a two fixed-term one-year contracts with Scion and VITO, with one year spent in New Zealand and one in Belgium.
 

MSCA-PF 2021 CALL: Technical and clinical validation of urinary EV protein biomarkers for the early diagnosis and follow up of bladder cancer.

Mol
Postdoc
Description: 

Context and research challenge

The current gold standard methods to diagnose a bladder cancer are cystoscopy and urine cytology. Cystoscopy has a low sensitivity for flat carcinoma in situ, which resembles an inflammation site. Cystoscopy is also operator dependent, especially for the detection of recurrence. This procedure is invasive and patients encounter anxiety. Urine cytology is non-invasive but fails to provide strong negative predictive value for low-grade tumors. Cytological interpretation is also user dependent and can be hampered, for example, by low cellular yield, urinary tract infections, and stones. Due to the high risk of relapse, intensive follow-up of these patients is recommended.

Urine biomarkers are an attractive alternative for the detection of bladder cancer.

In a previous phd project at VITO, non-targeted shotgun tandem MS was used to identify potential protein biomarkers in urinary small extracellular vesicles (sEVs) for (1) the diagnosis of a first bladder cancer tumor and (2) the follow-up of patients to detect a bladder cancer relapse. This resulted in a list of proteins that were differentially expressed. These data now needs technical and clinical validation, since protein biomarkers allow the easy and fast diagnosis of biomarkers in antibody-based assays.

Approach

  1. Urine samples of related urological pathologies will be collected in the clinic to filter the biomarker candidates for BC selectivity
  2. In parallel, an independent cohort of BC patients will be selected in a multicenter study and urine samples will be stored for validation purposes
  3. Diagnostic performance of a statistical model that will be based on a selection of best performing biomarker will be validated on the independent BC patient cohort
  4. An easy to use urine based diagnostic test (including a new statistical model) will be developed together with an external partner + benchmarked to the LC-MS based statistical model
  5. Clinical validation of the POC test
  6. Commercialization of the test

With this call, we invite researchers to submit their resumé (including track-record) and a one-page project description, that will be the basis for selecting candidates with whom we will collaborate for developing a competitive MSCA-PF proposal. 

Collaborations

The PhD project that proceeded this project was a collaboration with UAntwerpen. For the collection of clinical samples, we have ongoing collaborations with UZA, AZMM Gent, AZ Herentals and Turnhout. The network of hospitals will be further extended.

For the development and clinical validation of the PoC test, we ongoing collaborations with companies.

Deadline application to VITO

Interested candidates should submit their resume (incl. track record) and a one-page note describing the project for which a Marie Curie grant will be applied, as soon as possible and no later than Friday 30 April 2021 17h Brussels time.

Supervisor

Successful candidates will be supervised by Prof. Inge Mertens, coordinator of the Centre for Proteomics, a collaboration between VITO and UAntwerpen.

 Further information can be obtained from Prof. Inge Mertens: Inge.Mertens@vito.be

Deadline MSCA-PF 2021

Wednesday 15 September 2021 17h Brussels time.

Target start date

The EU informs the results on the MSCA-PF applications in February 2022. Successful candidates are expected to be available to start within the following two months and no later than summer 2022.

 

MSCA-PF 2021 CALL: Extending the Lifetime of Lithium-ion Batteries for Vehicle-to-Grid (V2G/V2X) Applications based on Robust Feedback Control.

Genk
Postdoc
Description: 

Context and research challenge

Renewable energy technologies allow for clean and sustainable energy to be harnessed from widely available self-renewing resources. However, their variable and intermittent nature leads to challenges to keep supply and demand in balance in the electricity grid at different physical and economical levels. To preserve this balance with an increasing share of renewables in the energy system, there is a growing need for flexibility. Next to the flexibility provided by conventional power plants, (inter)national interconnectivity, demand response, curtailment, energy storage is proving to be a potential valuable solution[1].

Batteries, being a form of electrochemical energy storage, are drawing more and more attention since they present promising characteristics to be applied at different physical locations, at different scales and for multiple services[2]. Around the world, batteries are being deployed for wider ancillary services such as frequency regulation, and also for peak shifting and supporting renewable energy production plants, to name but a few [3].

The state-of-the-art Li-ion technologies that are used for energy storage solutions are to a large extent the result of the developments made in an ever growing market for electric vehicles (EV),driven by international sustainability goals, market competition and more stringent mobility regulation. Demand for batteries in the EV market, and hence for critical materials they are partly made of, are largely exceeding the demand in the stationary energy storage market, which indicates a growth risk. Moreover ,prices for batteries have been declining over the recent years as production volumes are ramped up. However, investment costs are too high for offering economically viable use cases, especially at the residential level[4]. Therefore, questions are raised on the rate of deployment of batteries for energy storage purposes.

A smart integration of electric vehicles in the electricity system might be the solution. While they are in the first place acquired to answer a mobility need, they can also serve a flexibility need. More and more automotive OEMs are presenting vehicles that not only can be charged from the grid but also can deliver energy back to the system, being at a home, building or the electricity grid in general[5-6]. The latter process of discharging energy from the EV battery via a bidirectional charging system is referred to as vehicle-to-grid/home/building (V2G, V2H, V2B), in general V2X[7-8].

In addition to the provision of ancillary services,V2Xtechnologies can allow the integration of renewable energy sources in smart grids, save energy costs, and open new energy trading markets, using energy storage as a service[9].The economic viability of V2X services, however, depend on the financial profitability of the service for the end customers and aggregators, to name but a few. While some EV-types that facilitate such services using V2X technologies are commercially available, the influence on the lifetime of Li-ion batteries is often disregarded[10]. However, this has a big impact on the financial profitability of the service and therefore the uncertainty has to be tackled so that end-users can be convinced to use their EVs in V2X services.

Approach

This research will address a new approach of using optimal control in using the EV battery for trade on the electricity market, maximizing revenues and lifetime extension while preserving the level of comfort and safety for the end-user. This has to ‘warm’ the owner to provide his EV for these services.

With this call, we invite researchers to submit their resumé (including track-record) and a one-page project description, that will be the basis for selecting candidates with whom we will collaborate for developing a competitive MSCA-PF proposal. 

Collaborations

This research work will be performed in the multi-disciplinary energy unit within VITO connecting e.g. battery expertise with knowhow on optimization and control. This work also positions itself in existing and to be acquired international research and innovation projects.

Supervisor

Successful candidates will be supervised by Dr Sajjad Fekriasl. Dr Fekriasl has over 20 years of experience leading, conducting and communicating research, with both academia and industry, in the domain of Electrical Engineering and its wider real-life applications. Sajjad’s research interests cover modeling, development of estimation algorithms and advanced control systems with focus on robust control. His current activities include state estimation and control systems design for lithium-ion battery management systems, for both mobile and stationary battery energy storage applications.

Further information can be obtained from Dr. Sajjad Fekriasl via e-mail: sajjad.fekriasl@vito.be.

Deadline application to VITO

Interested candidates should submit their resume (incl. track record) and a one-page note describing the project for which a Marie Curie grant will be applied, as soon as possible and no later than Friday 30 April 2021 17:00 Brussels time.

Deadline MSCA-PF 2021

Wednesday 15 September 2021 17:00 Brussels time.

Target start date

The EU informs the results on the MSCA-PF applications in February 2022. Successful candidates are expected to be available to start within the following two months and no later than summer 2022.

MSCA-PF-2021 CALL: Genomics in Clinical Practice.

Mol
Postdoc
Description: 

Context and research challenge

The term “precision medicine” is coined to define health and disease on the individual level in great detail, in an effort to maintain health and prevent/delay the onset of disease(s). The crucial aspect in this endeavor is to be able to collect diverse and meaningful longitudinal data for each individual to define systemically, health and disease by assessing both genetic and environmental factors as well as the interactions among them. The central hypothesis of precision medicine is if we can map these factors on the individual level we can come up with tailored therapies for this individual.

Challenge

So the ideal of precision medicine highly depends on accurately assessing the unique features that separates this individual from his/her peers. In practice however, clinical tests ( offered by professional accredited labs) are designed with the purpose to diagnose diseased individuals from healthy individuals. The first technology that is mature enough to become part of daily clinical practice is personal genome. If genomics and clinical lab. tests are integrated correctly, it has the potential to impact on every aspect of clinical practice where clinical laboratory tests are used including preventative measures, diagnosis, therapy to interpretation of the results of clinical trials.

Approach

In this state-of-the-art project we are going to integrate genomics level differences across individuals with the clinical level data, with the aim of interpreting the clinical laboratory tests more accurately taking genomic differences in to account. For this purpose we are going to use a unique longitudinal dataset (including 100+ monthly clinical lab tests and Next Generation Sequencing [NGS]) collected via the “I am Frontier” pilot cohort at VITO and other cross sectional datasets available.

With this call, we invite researchers to submit their resumé (including track-record) and a one-page project description, that will be the basis for selecting candidates with whom we will collaborate for developing competitive MSCA-IF proposals. 

Collaborations

Within the context of this project, we are collaborating with University College London (UCL), University of Hasselt and Domus Medica (The association of General Practitioners in Flanders) where secondments/ research visits will be encouraged.

Deadline application to VITO

Interested candidates should submit their resume (incl. track record) and a one-page note describing the project for which a Marie Curie grant will be applied, as soon as possible and no later than Friday 30 April 2021 17h Brussels time.

Supervisor

Successful candidates will be supervised by Dr. Gökhan Ertaylan. Dr. Ertaylan has completed his PhD in the Computational Science department at the University of Amsterdam. After working in Luxembourg Centre for Systems Biomedicine, as a Marie Curie fellow and in Maastricht University, as a Senior Researcher, he has joined VITO to lead the efforts in Data Analysis and Integration in Systems Biology projects.

Email: gokhan.ertaylan@vito.be; Tel: +32 14335270

Deadline MSCA-PF 2021

Wednesday 15 September 2021 17h Brussels time.

Target start date

The EU informs the results on the MSCA-PF applications in February 2022. Successful candidates are expected to be available to start within the following two months and no later than summer 2022.

 

MSCA-PF 2021 CALL: Multiplex assay for extracellular vesicles-based early diagnosis of dementia-related syndromes.

Mol
Postdoc
Description: 

Context and research challenge

The current clinical approach for differential diagnosis of Dementia-related syndromes (DRS) is based on an arbitrary distinction between the time of onset of motor and cognitive symptoms. However, the need of more specific biomarker-based technologies for early diagnosing and following up DRS in affected patients is becoming imperative. 
Extracellular vesicles (EVs) have been shown to play a role in the mechanisms behind neurodegeneration and neuronal loss, and to hold promise as new biomarkers and therapeutic targets for DRS. Adequate technologies to fully exploit the potential of specific EVs subsets in the clinic are needed. The goal of the project is the development of a multiplex biomarker-based toolkit for targeted isolation and detection of EV subsets from liquid biopsies for DRS differential diagnosis.

Approach

Starting from a DRS-related EV biomarker profile, identified by clinical discovery proteomics at VITO, high-affinity binders will be selected and an adequate labeling approach designed to obtain optimal signal output for biomarker detection at the single EV level using high-sensitivity flow cytometry. Based on successful detection of individual biomarkers, a strategy for multiplexing will be designed and tested. Using the acquired knowledge of DRS-specific targeting molecules, also a sorting method for direct, selective purification and enrichment of EV subsets from liquid biopsies will be optimized. The performance of the toolkit components will be assessed on a set of EV isolates from different sample matrices (cerebrospinal fluid, plasma) of the original biomarker discovery and validation studies, and compared with targeted LC-MS and other, conventional techniques (ELISA, Western Blot).

With this call, we invite researchers to submit their resumé (including track-record) and a one-page project description, that will be the basis for selecting candidates with whom we will collaborate for developing a competitive MSCA-PF proposal. 
 
Collaborations

For the clinical test case of DRS, the EV biomarker panel and clinical sample access, collaboration with the team of Prof. Inge Mertens (VITO/UA Centre for Proteomics) is established. Furthermore, we foresee collaboration with Amsterdam University Medical Center (The Netherlands) for a dedicated secondment on standardization of high-sensitivity flow cytometry workflows for EV analysis in clinical samples.


Deadline application to VITO

Interested candidates should submit their resume (incl. track record) and a one-page note describing the project for which a Marie Curie grant will be applied, as soon as possible and no later than Friday 30 April 2021 17h Brussels time.

Supervisor

Successful candidates will be supervised by Dr. Inge Nelissen, Team leader Nanobiotechnology. 

contact: inge.nelissen@vito.be

Deadline MSCA-PF 2021

Wednesday 15 September 2021 17h Brussels time. 

Target start date

The EU informs the results on the MSCA-PF applications in February 2022. Successful candidates are expected to be available to start within the following two months and no later than summer 2022.

MSCA-PF 2021 CALL: Exploring new analytical frontiers in the characterisation of micro- and nanoscale non-metallic particles.

Mol
Postdoc
Description: 

Context and research challenge

The characterisation of micro- and nanoscale particles is of great interest to a broad spectrum of industrial and environmental applications. The continuous technological improvements in analytical instruments have ignited new analytical ideas and pathways to assess and explore several key characteristics, such as concentration, composition, particle size, shape and other surface characteristics. The in-depth mass spectrometry and size separation chromatography knowledge present in the VITO laboratory, has been successfully used to explore new characterization approaches for nanoscale metallic particles in different VITO related R&D case studies (e.g. (a) (bi-)metallic nanoparticles used for reductive catalytic depolymerisation of lignin, (b) glycan-functionalised gold nanorods used in health diagnostics).
This does however not fulfil the characterisation needs for non-metallic nano- and micro scale particles. They require another approach due to the nature of the molecules involved. The goal of this project is to open up new frontiers regarding characterization of non-metallic micro- and nanoparticles (1nm-20µm). The achievement of these goals will require a wide set of complementary tools such as analytical and instrumental chemistry, physics and nanometrology.

Approach

Method development will be performed on existing instrumentation available at GOAL . This includes mass spectrometry based instrumentation, i.e. single particle ICP-MS and pyrolysis–gas chromatography–MS; size separation chromatography instrumentation, i.e. size exclusion chromatography – UV/VIS – multi angle light scattering and FT-IR.  

The (not-limitative) envisaged VITO R&D applications/collaborations are : 
Characterisation of microplastic particles/fibres during development phase of a VITO microplastic filtration unit for washing machines.  Microplastic pollution caused by washing synthetic textiles is one of the main sources of primary microplastics (~ a third of all primary microplastics released to world oceans).

With this call, we invite researchers to submit their resumé (including track-record) and a one-page project description, that will be the basis for selecting candidates with whom we will collaborate for developing a competitive MSCA-PF proposal. 
 

Deadline application to VITO

Interested candidates should submit their resume (incl. track record) and a one-page note describing the project for which a Marie Curie grant will be applied, as soon as possible and no later than Friday 30 April 2021 17h Brussels time.

Supervisors

Successful candidates will be supervised by Prof. Dr. Stefan Voorspoels and Dr. Kristof Tirez.

Prof. Dr. Stefan Voorspoels is team leader of the analytical team and project manager of several research projects in the field of chemical analysis and method development, human exposure, chemical and material characterization. He is also visiting professor “Analytical Chemistry” at the Faculty of Engineering and Architecture at Ghent University. He is specialized in organic analytical chemistry and chromatography.

Dr. Kristof Tirez works as a researcher and project leader in the inorganic analytical department of Vito. His main experience and research interests are situated in the quantitative determination and speciation of elements in a variety of matrices. Besides, he acts as a science - policy bridge person and analytical expert for different Flemish agencies dealing with environmental regulatory monitoring. 
For any inquiries please contact: kristof.tirez@vito.be

Deadline MSCA-PF 2021

Wednesday 15 September 2021 17h Brussels time.

Target start date

The EU informs the results on the MSCA-PF applications in February 2022. Successful candidates are expected to be available to start within the following two months and no later than summer 2022.

MSCA-PF 2021 CALL: Microfluidic device for self-sampling of blood for human biomonitoring applications.

Mol
Postdoc
Description: 

Context and research challenge

VITO plays an important role in human biomonitoring on the Flemish (FLEHS studies) and European level (H2020 HBM4EU project), and is involved in the preparation of the European Partnership for the Assessment of Risks from Chemicals (PARC).  In one of the work packages of PARC, ‘Innovative methods and tools for monitoring and surveys’ will be developed. VITO and KUL will collaborate to develop a self-sampling device for analysis of chemicals in small blood volumes. The technology is ideal for use by non-trained personnel and allows mass production fabrication (i.e. roll-to-roll), which lowers its production cost to < 5 €/device.

Approach

An existing microfluidic chip will be adopted to allow user-friendly and remote (at home) self-sampling of capillary blood. This chip can be used, as nowadays assessment of chemicals is possible in small blood/ plasma volumes of tens of microliters. The sampling chip is patented by KUL, based on the (i)SIMPLE technology (see picture). (i)SIMPLE combines a microfluidic channels network with passive paper-based pumps, enabling precise pushing and pulling of liquids. In particular, on the chip, two different modules will be developed and eventually integrated. First, a blood to serum/plasma filtration module is optimized. Second, a module is optimized to mix on-chip standards of a chemical, needed for LC-MS/MS analysis. Sampling cartridge performance (e.g. serum/plasma volume, type of standards, storage conditions) is optimized towards maximum compatibility with the downstream laboratory analysis.

With this call, we invite researchers to submit their resumé (including track-record) and a one-page project description, that will be the basis for selecting candidates with whom we will collaborate for developing a competitive MSCA-PF proposal. 

Collaborations

Secondment (3 months, spread over the 2-years) to Department of Biosystems – Biosensors Group 
KU Leuven – University of Leuven

Deadline application to VITO

Interested candidates should submit their resume (incl. track record) and a one-page note describing the project for which a Marie Curie grant will be applied, as soon as possible and no later than Friday 30 April 2021 17h Brussels time.

Mail your interest to: Dr. Ir. Gudrun Koppen, project leader in Human Biomonitoring projects, and Dr. Stefan Voorspoels, project leader in Chemical Analytics. E-mail addresses: gudrun.koppen@vito.be and stefan.voorspoels@vito.be.

Deadline MSCA-PF 2021

Wednesday 15 September 2021 17h Brussels time. 

Target start date

The EU informs the results on the MSCA-PF applications in February 2022. Successful candidates are expected to be available to start within the following two months and no later than summer 2022.

MSCA-PF 2021 CALL: Embedding Physics-Based Modelling in Battery Management Systems to Improve Battery State Estimation and Control.

Genk
Postdoc
Description: 

Context and research challenge

More and more applications are powered or supported by batteries. Think of electric cars, bikes, buses and trucks but also ships, cranes and forklifts and stationary energy storage systems enabling higher shares of renewable energy in the electricity system.

More than 80% of newly installed battery capacity is based on lithium-ion battery technology, primarily based on LiFePO4 (LFP)or LiNixMnyCo1-x-y (NMC) cathode materials, given their superior combined techno-economical characteristics over alternative technologies. However, their operation inherently comes with a safety risk since those batteries contain flammable material. Therefore the battery shouldn’t be operated outside a Safe Operating Area (SOA), or safe operating window, typically expressed in terms of voltage, current and temperature limits. To enable safe battery operation, the battery is equipped with a battery management system (BMS) that is not only monitoring the battery parameters but typically also providing control and protection functions, communication interfaces and battery diagnostics. The total system approach for batteries as defined in our group is given in Figure1.

In nowadays applications, the SOA and its limits are at best set in a dynamic way and dependent on the actual use of the battery, the operating conditions and the state of the battery. The latter can refer to the State of Charge (SoC) but also the State of Health (SoH) of the battery and those battery states are often estimated by the BMS based on simple battery models with low computational burden that can be hosted on BMS processors. However, given the uncertainties on the actual state estimation of the battery, the SOA limits, or boundaries, are chosen in a conservative way limiting the intrinsic possibilities of the battery in terms of power and/or energy capabilities. This limiting factor ultimately has an impact on the economic viability of the battery based solution.

Approach

The end goal of the research track on advanced physics-based battery modelling is to have the models embedded in BMS algorithms that can be applied in real-time battery control for various applications(e.g.(fast) charging of vehicles and ancillary services with energy storage) leading to an improved techno-economical offering as compared to the state-of-the-art.

This research work builds on the current expertise of the team and will focus on different aspects. The first task will to be reduce the computational burden of the physics-based battery model so that it can be embedded on a BMS to assist in an improved battery state estimation, SoC, SoH and SOA. Another task will be the support of the battery control based on those models so that eventually a closed loop control can be hosted or at least contributed by the BMS taking into account accurate state estimation. A third task will be situated in the adaptation of the model based on the comparison of battery monitoring and model prediction to continuously improve on the offering.

With this call, we invite researchers to submit their resumé (including track-record) and a one-page project description, that will be the basis for selecting candidates with whom we will collaborate for developing a competitive MSCA-PF proposal. 

Collaborations

This research work will be performed in the multi-disciplinary energy unit within VITO connecting e.g. battery expertise with knowhow on optimization and control. This work also positions itself in existing and to be acquired international research and innovation projects.

Supervisor

Successful candidates will be supervised by Dr Sajjad Fekriasl. Dr Fekriasl has over 20 years of experience leading, conducting and communicating research, with both academia and industry, in the domain of Electrical Engineering and its wider real-life applications. Sajjad’s research interests cover modeling, development of estimation algorithms and advanced control systems with focus on robust control. His current activities include state estimation and control systems design for lithium-ion battery management systems, for both mobile and stationary battery energy storage applications.

Further information can be obtained from Dr. Sajjad Fekriasl via e-mail: sajjad.fekriasl@vito.be.

Deadline application to VITO

Interested candidates should submit their resume (incl. track record) and a one-page note describing the project for which a Marie Curie grant will be applied, as soon as possible and no later than Friday 30 April 2021 17:00 Brussels time.

Deadline MSCA-PF 2021

Wednesday 15 September 2021 17:00 Brussels time.

Target start date

The EU informs the results on the MSCA-PF applications in February 2022. Successful candidates are expected to be available to start within the following two months and no later than summer 2022.

 

MSCA-PF 2021 CALL: Orchard digital twins from drone- and tractor-based imagery.

Mol
Postdoc
Description: 

Context and research challenge

Growers are expected to increase their fruit production with higher quality at lower expenses in a sustainable way that is less dependent on labour force. By 2050, the agri-food sector must generate 50% more food and feed due to increased demand.[1] Fruit growers need many seasonal workers to perform tedious manual tasks, including pruning, thinning flowers or fruitlets and harvesting. However, society has moved away from living in rural areas to people living in cities now; as a result, agricultural companies are facing the challenge of workforce higher costs or even shortages. The EU agricultural outlook of the European Commission (2018) predicts that labour outflow from the agricultural sector will continue until 2030. The outlook suggests that the agricultural workforce will reach 7.7 million workers in 2030, with a yearly decline of 2% by 2030. The recent new coronavirus COVID-19 outbreak causes a dramatic shortfall in workers because of the border restrictions put in place to stem the spread of the virus. The restriction of the movement of seasonal workers could cause far-reaching and long-term impacts on the agri-food sector and could extend “well beyond this year.”[2] Not to mention that besides a lower availability of seasonal workers, labour costs only increase, which is not compatible with low fruit prices. A promising solution to help with this shortage of workers and high labour costs is the use of agricultural robots integrating Artificial Intelligence (AI).

The main challenges for current state of the art robotics in agriculture include (1) operating in varying and unstructured environments (e.g., occlusion, fruit clustering, changes in canopy and light conditions), (2) assuring operational safety and efficiency, (3) interaction with deformable plants, (4) adequate skill and knowledge required to implement robotic field operations effectively and efficiently[3]. To tackle these challenges, simulation environments and methods can provide an alternative for experimenting with different sensing and end effectors to verify the performance functionality of the robot in such diverse scenarios. This offers a reliable approach to bridge the gap between innovative design and field trials, and therefore can accelerate the development of a robust agricultural robotic platform and the evaluation of novel sensing and control algorithms. Technological advances over the last few years have greatly increased our ability to collect, collate and analyse data on a per-tree basis at large orchard scales. This can also be called a “Digital-Twin Orchard”. A digital-twin is a virtual model of every tree and surroundings. The pairing of the virtual and physical worlds allows analysis of data and continuous monitoring of orchards production systems, and to develop new opportunities for end-to-end learning. Monitoring of orchards is not a new concept but the digital-twin is a continuously learning system that could be queried automatically to analyse specific outcomes under varying simulated environmental and orchard management parameters. So, to avoid expensive redesigns and shorten the critical time to market, virtual prototyping and testing in a virtual digital twin world opens up tremendous opportunities for robotics in agriculture. 

Approach

Drone and tractor based image processing. Use of a stereo camera mounted on a small tractor platform to automatically build depth maps of the orchard, extracting 3D information for structural parameter extraction,  and accurate flower and fruit counting to predict yield.  Information extraction will involve using deep learning algorithms for object detection, building on the deep learning expertise of VITO from other projects.

With this call, we invite researchers to submit their resumé (including track-record) and a one-page project description, that will be the basis for selecting candidates with whom we will collaborate for developing a competitive MSCA-PF proposal. 

 Collaborations

Udl, Lleida, Spain - Pcfruit, St Truiden, Belgium

Deadline application to VITO

Interested candidates should submit their resume (incl. track record) and a one-page note describing the project for which a Marie Curie grant will be applied, as soon as possible and no later than Friday 30 April 2021 17h Brussels time.

Supervisor

 Successful candidates will be supervised by Bart Beusen. Bart has been using deep learning since 2015 on various projects involving satellite, aerial and UAV data.

Bart Beusen – bart.beusen@vito.be/Remote Sensing and Earth Observation Processes/Phone: +3214335843

Deadline MSCA-PF 2021

Wednesday 15 September 2021 17h Brussels time.

Target start date

The EU informs the results on the MSCA-PF applications in February 2022. Successful candidates are expected to be available to start within the following two months and no later than summer 2022.

 

[3] Zhang, Q., Karkee, M. and Tabb A. (2019), The use of agricultural robots in orchard management, in Robotics and automation for improving agriculture, J. Billingsley, Ed. Burleigh Dodds Science Publishing, pp. 187–214. http://dx.doi.org/10.19103/AS.2019.0056.14

MSCA-PF 2021 CALL: Monitoring drought and drought impact with satellites.

Mol
Postdoc
Description: 

Context and research challenge

Climatic changes seemed to have a generally positive impact on agricultural productivity when water was not limiting. However, future climate changes are likely to include further increases in mean temperature (about 2–4 °C globally) with significant drying in some regions, as well as increases in frequency and severity of extreme droughts, hot extremes, and heat waves. Recent studies of increased crop mortality and die-offs triggered by drought and/or high temperatures suggest that at least some of the world’s agricultural ecosystems may be already responding to climate change. This raises concern that crops may become increasingly vulnerable in response to future warming and drought, even in environments that are not normally considered water-limited such a Belgium.

In Belgium, water use for irrigation has increased significantly the past years, putting additional pressure on the already limited water resources. To properly understand the impact of drought in agricultural production, advanced remote sensing systems will be developed. Main focus will be on the detection and monitoring of stress phenomena across a wide range of site conditions, as well as the quantification of yield losses as a result of these stresses. It holds a strong potential for identifying priority areas for implementing suitable adaptation strategies.

Approach

Use of satellite image processing techniques to monitor drought stress (temperature, evapotranspiration) as well as quantify yield losses.

With this call, we invite researchers to submit their resumé (including track-record) and a one-page project description, that will be the basis for selecting candidates with whom we will collaborate for developing a competitive MSCA-PF proposal. 

 Collaborations

Belgian agronomical research centres, Insurance companies

Deadline application to VITO

Interested candidates should submit their resume (incl. track record) and a one-page note describing the project for which a Marie Curie grant will be applied, as soon as possible and no later than Friday 30 April 2021 17h Brussels time.

Supervisor

Successful candidates will be supervised by Laurent Tits. He obtained his master in Bioscience Engineering in 2009 and his PhD in 2013 at the KU Leuven, Belgium, where he focused on the use of EO data in orchards. He is currently the team leader of the agricultural applications team at VITO Remote Sensing, Belgium. With his team, current agricultural applications of EO data encompass the broad range of very precise UAV data for detailed monitoring and phenotyping, up to the general monitoring of all the agricultural production areas on a global scale and everything in between. The activities encompass both reseach and feasibility studies as operational services.

Further information can be obtained from Laurent Tits via e-mail: Laurent.tits@vito.be

Deadline MSCA-PF 2021

Wednesday 15 September 2021 17h Brussels time.

Target start date

The EU informs the results on the MSCA-PF applications in February 2022. Succesful candidates are expected to be available to start within the following months and no later than summer 2022.

MSCA-PF 2021 CALL: Drone and tractor-based image analysis to support precision farming.

Mol
Postdoc
Description: 

Context and research challenge

The fruit sector's competitive position in Flanders can only be retained by an increase in rentability of the fruit growing companies. While human judgment might always be needed to some degree, autonomous robots, including drones, could take a lot of the hard, repetitive work out of fruit farming. By using the power of the digital age to handle large amounts of data, crops can be dealt with as individual plants rather than on a field-wide basis. Applying fertilizer, irrigation, herbicides, and pesticides in more targeted ways could reduce costs for farmers and ensure plants get the right amount of each treatment. Furthermore, efficient and accurate flower and fruit counting supports yield prediction. This latter has importance to the industry in planning market needs and resources, such as crop insurance purposes, packing materials, planning harvest, and employees. Furthermore, the industry needs to book transport, estimate cash-flow budget, and plan delivery estimates to ensure a faster turnaround to lessen the waste of time and resources.

The required data can be generated by sensors mounted on tractors/robots or drones or through satellite images. Camera and sensor technology have recently been evolving steadily and offer many opportunities to increase the fruit sector's competitiveness. The applicability or success of precision agriculture depends on the availability of appropriate data and how information is translated into treatment measures.

Approach

Hyperspectral and RGB drone and tractor-based data is available from ongoing projects in which the aim is to (1) detect Red Palm Weevil (RPW) infestations in palm trees in Spain and Saudi Arabia; (2) detect fire blight infections in pear orchards in Belgium; (3) monitor pear fruit production throughout the season in Belgium. 

By extending existing artificial intelligence algorithms for hyperspectral imagery, this research topic aims to develop a method to detect different objects in a fruit/ palm tree.

  • A map of leaf objects can be used to steer pruning and precision spraying in fruit trees and to analyze the spectral behavior of different leaf age classes in palm trees
  • A map of fruit objects will help in predicting yield
  • A map on flower objects can steer flower/ fruit thinning
  • A map with healthy and diseased objects can steer precision herbicide and pesticide spraying, precision irrigation and fertilization.

An expected outcome is the development of an AI based image processing chain for (diseased) object detection in fruit orchards.

With this call, we invite researchers to submit their resumé (including track-record) and a one-page project description, that will be the basis for selecting candidates with whom we will collaborate for developing a competitive MSCA-PF proposal. 

 Collaborations

King Abdullah University of Science and Technology (KAUST), Saudi Arabia - Phoenix research Station (PRS), Spain - Pcfruit, St Truiden, Belgium - WUR, the Netherlands - KULeuven, Belgium - IMEC, Belgium - FlandersMake, Belgium

Deadline application to VITO

Interested candidates should submit their resume (incl. track record) and a one-page note describing the project for which a Marie Curie grant will be applied, as soon as possible and no later than Friday 30 April 2021 17h Brussels time.

Supervisor

Successful candidates will be supervised by dr. Stephanie Delalieux (Scopus h-index: 18): Stephanie Delalieux obtained her PhD degree in Bioscience Engineering, Department of Biosystems in 2009 from the KULeuven (BE). During her PhD, she zoomed in on early stress detection in fruit orchards using hyperspectral image analysis. Today, Stephanie continues her passion for the field as a senior researcher at VITO Remote Sensing. Her main research interests include the use and application of high spectral, high spatial and high temporal resolution remote sensing data for precision agriculture and biodiversity applications. She has coordinated several research and commercial projects and has supervised more than 10 MSc and 4PhD students.

Further information can be obtained from dr. Stephanie Delalieux via e-mailStephanie.Delalieux@vito.be

Deadline MSCA-PF 2021

Wednesday 15 September 2021 17h Brussels time.

Target start date

The EU informs the results on the MSCA-PF applications in February 2022. Successful candidates are expected to be available to start within the following two months and no later than summer 2022.

MSCA-PF 2021 CALL: Hybrid Deep Learning control to support the participation of aggregator of a large number of prosumers.

Genk
Postdoc
Description: 

Context and research challenge

Recent years have seen an increasing interest in Demand Response (DR) as a means to provide flexibility and increasing the penetration of renewable resources in the power system. Aggregators are being lauded as critical in enabling DR to provide these valuable electricity services at scale.  At the aggregator level,  where there is a multitude and variety of devices and appliances across the aggregator’s portfolio (building HVAC, PVs, EVs, water tanks etc), the process of control and scheduling is rendered infeasible without automating a big part, or the whole process.

The bigger challenges of the whole control and scheduling problem for the aggregator are:

  • real-life DR systems are increasingly an aggregation of a large number of heterogeneous systems, users and devices. Modelling such heterogeneous system is infeasible for three main reasons:  (i) the lack of complete information and data from the different components, (ii) the traditional approaches (mainly from the mathematical optimization and control theory) results in complex and intractable problems as the number of devices and therefore the variables involved increase, and (iii) there are many sources of uncertainty (e.g. dynamic prices, user behavior,  availability of renewables etc.) which introduce additional complexities to the ones described to the previous point;
  • the increasing integration of renewable resources in the electric power grid has increased the need for producers and virtual producers (i.e. aggregators) to offer/trade or correct their offer close to real-time in order to better deal with the high uncertainty due to the availability of renewables. However, the  current approaches (MILP, MPC etc.) cannot guarantee a good ‘anytime’ solution for real-time control and scheduling due to the aforementioned computational issues.

Approach

In this project, innovative methods need to be researched and initiated to design to optimally schedule and control aggregator’s portfolio with a numbers of heterogeneous prosumers for DR schemas.

Particularly, the successful candidate will have the aim to research and design new hybrid approaches that combine modern machine learning methods (e.g. deep reinforcement learning) and optimal control approaches (e.g. model predictive control) to address the challenges faced by the uncertainty and  the complexity of coordinating a large number of prosumers.

With this call, we invite researchers to submit their resumé (including track-record) and a one-page project description, that will be the basis for selecting candidates with whom we will collaborate for developing a competitive MSCA-PF proposal. 

Collaborations

This research is performed within the framework of EnergyVille, a research collaboration on sustainable energy between VITO, KU Leuven, Imec and UHasselt.

Deadline application to VITO

Interested candidates should submit their resume (incl. track record) and a one-page note describing the project for which a Marie Curie grant will be applied, as soon as possible and no later than Friday 30 April 2021 17h Brussels time.

Supervisor

Dr. Carlo Manna is a researcher in applied artificial intelligence for energy systems. He  had experience as senior researcher in academia (University College Cork 2011-2017) and as R&D scientist in industry (ZF-Automotive AG 2017-2019). Hi is co-authored of more than 30  journals/peer-review proceeding publications listed in Scopus and 7 German/US patents applications.

Successful candidates will be supervised by Dr. Carlo MannaFor any inquiries please contact Dr. Carlo Manna at carlo.manna@vito.be.

Deadline MSCA-PF 2021

Wednesday 15 September 2021 17h Brussels time.

Target start date

The EU informs the results on the MSCA-PF applications in February 2022. Successful candidates are expected to be available to start within the following two months and no later than summer 2022.

Postdoc @ VITO

We offer you an outstanding research environment at the interface between the field of academic research and the applied industry.

Take a look at the postdoc topic list to see what VITO has in store for you.

VITO regularly launches a call for candidates who would like to do research as a postdoc researcher that supports the strategic research of VITO.

A postdoc in the framework of the Marie Sklodowska-Curie program

VITO supports candidates who have already obtained a doctorate and who wish to apply for a scholarship within the framework of Marie Sklodowska-Curie, or for another grant. International exchanges are an asset in this case.