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Field
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of metabolic network modelling linked to epigenetics Carry out machine learning, and integrative analysis of large epigenome datasets Communicate research results in international conferences and journals Work
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, partly due to a lack of reliable predictors of transplantation outcomes. The ADORABLE consortium aims to develop an advanced, data-driven assessment system for donor kidneys. Central to this is the use
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reasoning domains. This work will blend cutting-edge experimentation - spanning RL, few-shot learning, meta-learning, etc. - with formal analysis to push the boundaries of what modern AI systems can reliably
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for graphs; 4. Practical experience in the analysis of scientific data; 5. Proficiency in programming with Python; 6. Familiarity with the drug discovery process; 7. Ability to work on interdisciplinary
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through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description This work is part of the PEPR Math-Vives
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. Our research is rooted in basic research and centres on mathematical models of the physical and virtual world, as a basis for the analysis, design, and implementation of complex systems. We focus
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, or erroneous data, Data cleaning and generation, Development of enhanced loss functions and information-theoretic methods for optimized data analysis, Machine learning-based image segmentation of tomographic
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led by Dr. Danick Briand from the Soft Transducers Laboratory at the EPFL (Swiss Federal Institute of Technology) has PhD students openings in the fields of wearable biosensors for saliva analysis
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-equilibrium conditions. The project is a UKRI/NSF collaboration with Virginia Tech, and the use of direct numerical simulation, modelling and analysis will be complemented with experimental data from
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trade-offs and maximizes synergies between landscape services. In this PhD project you will develop this innovative theory and combine spatial analysis with a Research Through Design approach. You first