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correlations, characterizing disease progression, and exploring early disease changes. This knowledge is crucial to improve prognosis, patient care guidance and support the development of future gene-based
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Saelens team. Research Project In this research project you will develop probabilistic deep-learning models that automatically extract biological and statistical knowledge from in vivo perturbational omics
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Qualification: The candidate should possess an MSc degree or equivalent in Telecommunications and Computer Science. Experience: The ideal candidate should have some knowledge and/or experience in several
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proficiency for both written and verbal communication. Knowledge of French, German and/or Luxembourgish is not required. We offer Multilingual and international character. Modern institution with a personal
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knowledge of wireless communications, and signal processing. You have at least intermediary knowledge of machine learning algorithms, including federated learning, split learning, and graph neural networks
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preferred. Good knowledge of English is essential. Candidates should be flexible to work at both host institutions, located ca. 50 km apart with a direct train connection in-between. This position is funded
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Personal Career Development Plan which includes (1) Training through individually personalized research projects under senior supervision (2) Exchanging knowledge with the scientific community and the
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. Strong knowledge of quantitative and/or computational research methods, ideally in econometric analysis or optimization and simulation models. Preferable knowledge in Python and STATA. A collaborative team
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dimensionality reduction as well as analysis of blood proteomic data. We are looking for a student with experience in bioinformatics and relevant statistical methods using R or Python languages. Some knowledge of
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in sensing, quantum technologies, and photonic design to define system concepts and specifications. Support the development of PIC layouts. Documentation and Knowledge Sharing: Prepare technical