Postdoc

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. 

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, before Friday 17 April 2020 17h Brussels time.

Deadline MSCA-IF 2020: Wednesday 9 September 2020 17h Brussels time.

Research challenge:
Current state-of-the-art approaches for probabilistic forecasting are either incapable of considering time-correlation, or make use of (too) rough assumptions about the Gaussian character of the involved stochastic disturbances. The research challenge is to develop performant and accurate probabilistic forecasting methods that overcome these drawbacks and use novel stochastic Machine Learning (ML) techniques to capture time-correlation without resorting to approximations, tackling the difficulties of scenario-based forecasting. Such ML techniques may include Deep Learning Networks, Neural Processes, Approximate Bayesian Inference, Hybrid Models etc.

Approach:
To be most efficient, the selected candidate will develop of these techniques focusing on the challenges emerging in a specific and particularly innovation driven domain of smart management and operation of low voltage distribution grids. In practice, these techniques will include novel beyond-state-of-the-art stochastic forecasting methods that can support the construction of live-scale, accurately finetuned and reliably robust digital twin (statistical simulation models) that capture the electrical aspects of the low voltage distribution grid. From the point-of-view of the distribution network operator, this approach tackles the most urgent challenges caused by the energy transition (electric vehicles, distributed electricity production, residential demand response, etc.), and has the added advantage of a high valorisation potential.

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
The need and opportunity for collaboration with other research institutions and with relevant partners in industry will certainly emerge and are even a necessity. This can potentially result in secondments at the premises of one or more such partners. Collaboration with Belgian and European DSO’s will probably turn out to be of the highest importance for relevant data-access.

• 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, before Friday 17 April 2020 17h Brussels time.

Deadline MSCA-IF 2020: Wednesday 9 September 2020 17h Brussels time.

VITO contact details:
Dr. Koen Vanthournout
Unit ETE / Group AMO / VITO - EnergyVille
VITO: Boeretang 200, 2400 Mol, Belgium NV (Headquarters)
EnergyVille 1: Thor Park 8310, 3600 Genk, Belgium (place of work)
tel: +32 14 33 59 16
 

In a CE, materials and products are reused as much as possible through recycling, repair, refurbishment and sharing of products and materials. However, a lack of data concerning the usage history and physical state of the products (or its components) and materials and sharing of data between the different partners of the value chain, often hinders the uptake of these CE strategies. Especially because of reluctance to share (sensitive) data among value chain actors, a blockchain can address the data-related issues as it allows to access other value chain actor’s data without revealing each other’s identity. In short, blockchains store data on the transaction of products, and data on the product itself in a distributed ledger, a system widely accepted for its data accuracy and data authenticity. In case the blockchain technology is combined with track and trace technology (e.g. monitoring or sensor technology), the blockchain can provide a means to guarantee the trustworthiness of the product data and ensure a link between the physical product and the accompanying data. As such, blockchain can assist in determining the (geographic) location, physical condition, track record of defects & repairs, and ownership status of materials, products, or products parts in the value chain.

The disclosure of this information is essential in order to allow the transactions within a circular economy which would previously be hindered by a lack of data. It is still to be investigated how this information should be processed and disclosed in real-time in order to allow optimal steering of circular transactions. At present, the circular economy struggles with these kind of questions, and often needs a middleman to answer them. This however increases the number of parties involved in the circular value chain and hence increases a circular system’s complexity and cost. The implementation of blockchain technology can avoid the introduction of the additional layers in the circular value chain (i.e. the role of middlemen) in case the blockchain technology can provide the necessary information to efficiently answer the repair or replace question.

Expectations:
The goal of the envisaged project is three(four)fold:

1. Identify potential circular economy innovations (business cases) which are currently complicated due to a lack of trust during the transaction phases, or currently rely upon the intervention of a middlemen;
2. Assess the potential of  blockchain as enabler of the endangered circular transactions, or reduce complexity by decreasing the need for a middle-men as transaction facilitator;
3. Assess the potential of a kind of automated circular decision making tool: the tool will make use of blockchain technology to distribute (e.g. sensory) data among the involved parties in a circular value chain. Artificial Intelligence will then be applied in order to automate the decision making, based upon the gathered data. Once the potential of these tools is analyzed, the project will investigate to what extent this kind of innovations will disrupt the current value chains and create new business model opportunities.
4. If deemed relevant for the research: Conclude a first estimate of the environmental impact of a blockchain driven circular innovation, balancing the environmental gains of increased circularity and environmental costs related to for example the energy use of the blockchain itself.

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
Discussions are running.

• 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, before Friday 17 April 2020 17h Brussels time.

• Deadline MSCA-IF 2020
Wednesday 9 September 2020 17h Brussels time.

Research challenge:
Pectin, a very common by-product of agro-industrial processes, is one of the polymers constituting the cell wall of higher plants. It is mostly constituted by galacturonic acid units linked by a-1,4-glycosidic bonds (polygalacturonan) that can be interspersed with rhamnose units (rhamnogalacturonan). Galacturonic acid hydroxyl groups can be partially methylated or acetylated. Other neutral sugars that can also be present in pectins are represented by galactose and arabinose. Different vegetal species have different pectin structures, generated by the combination of the different sugars, making pectin a very diverse and very heterogenous class of biopolymers.
Pectin can be exploited for the production of pectin oligosaccharides (POS). POS are usually generated by directed and tailored enzymatic hydrolyses, using different enzymes to degrade the different pectin regions. POS have been proven to have interesting biological properties, which mostly reside in their ability to positively interact with the gut microflora, and to give a specific stimulation of probiotic gut bacteria.
Unfortunately, the properties of POS very much depend on the specific composition, which, given the high diversity of pectin and the diverse enzymes used for POS production, can enormously vary among different starting materials and preparations. Given this diversity, the assessment of the biological properties is to be firmly related to the actual composition of the POS mixtures, in order to make clear links between the structure and the observed activity, and to define the most active POS. This in turn can allow to define which pectin is to be used as starting materials for POS. Moreover, the isolation of the targeted

Approach:
The project will have a twofold target. The first aim is to assess the potential prebiotic effect of diverse POS mixtures by microbiological tools and detailed analysis, allowing to define the most active POS structures. This task will partially rely on already existing in-house expertise, which will be complemented by specific expertise of the candidate in this field and a possible secondment in a specialized group. The second aim is to enrich the POS-preparations with the identified active compounds by fractionation using a new generation of functionalized membranes, purposely developed in the framework of this project, able to separate the different compounds in POS preparations according to charge, length and other physico-chemical properties. This main aim is to prepare prebiotic mixtures having high specific activity.

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.

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, before Friday 17 April 2020 - 17h Brussels time.

Deadline MSCA-IF 2020: Wednesday 9 September 2020 17h Brussels time.