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an advantage: plasma surface functionalization; electrode/electrolyte interfaces; battery degradation modelling; microstructure-resolved modelling; tomography or image-based electrode modelling; machine learning
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position The Laboratory of Causal Systems Immunology is looking for a PhD student or postdoctoral researcher to advance in vivo perturbational screening. We have developed single-cell CRISPR technologies
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conferences and publish in scientific journals You contribute to the supervision of PhD students working in these areas Your profile Excited to bring biology into the agentic era Broad interest across
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-culture in vitro models of the central nervous system. Experience with cell-based assays and plate-based screening. Strong track record of accurate data generation, documentation and experimental
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-culture in vitro models of the central nervous system. Experience with cell-based assays and plate-based screening. Strong track record of accurate data generation, documentation and experimental
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Your research is situated in the EU-funded Horizon Europe project EOSC-ARENA (AI Research Enhancement through Networked Agents), funded under the European Commission’s GenAI4EU initiative. The overall
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critical mind, and motivation are skills that are more than welcome Knowledge of both the basics and the latest developments of machine learning, in particular large language models and agentic framewoks
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, biomedical data science, digital health, epidemiology, and environmental health. The position focuses on the development, validation, and interpretation of AI models for health risk prediction using
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and adapt assimilation schemes based on generative deep learning methods (such as flow matching and diffusion models). The candidate should have previous experience in data assimilation and/or deep
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modelling approaches bridging EMT and system-level studies. The researcher will contribute scientifically through independent research, supervision of PhD students, publications in leading IEEE journals