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found on hpc.uni.lu . The activities include classical HPC applications such as simulation and modeling, but also artificial intelligence and machine learning, bridging computational science, with data
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modelling of complex plasma processes, contributing significantly to fields such as fusion reactor design, material deposition technologies, and space propulsion systems. The project brings together a
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. The project is led by Heiko Schütt and will employ one PostDoc and one PhD student. About the role... You will develop new Bayesian methods to compare models to neural data. You will test the methods
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under the guidance of Prof. Ivan Nourdin. Your role Conduct research in machine learning, deep learning, and probabilistic modeling, with a focus on real-world applications Disseminate research findings
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between fundamental research and integrative clinical care by embedding the "from bench to bed" research approach. Fundamental research focuses on iPSC-derived neuronal models to elucidate the molecular and
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. • Pr. Leif A. Eriksson, molecular modeling of protein complexes, University of Gothenburg, Sweden. Eligibility criteria – The fellowship obtained is part of the BIENVENÜE international post-doctoral
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structural equation models (SEM) or similar approaches Public outreach and open science activities Acting as scientific advisor for a doctoral researcher employed in the project Communication with partners and
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. Cutting-edge technologies will be used, including single-cell omics, high-dimensional imaging (CycIF, iDISCO), genomic editing, and functional validation in patient-derived brain organoids and murine models
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to conduct proof-of-principle research and characterize NPC pathway components in mouse models in the context of neurological disorders and cancer. How to apply: Applicants should hold a PhD in biology