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(CY Cergy Paris Université, AGM) and Marie Kratz (ESSEC, IDO dept. & CREAR), to contribute to the development and analysis of models within this broad framework. Located in the Paris area, the AGM
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, methodologically and empirically. Management and analysis of existing research data, optionally producing own empirical data, writing publications for scientific journals. Co-editing a book / special issue on
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in vivo genetic mouse models, advanced live and intravital imaging, engineered microchip models, primary cell co-culture systems and novel microscopy and analysis methods. The research will provide
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biophysical network models of The Virtual Brain (TVB) type, we aim to mechanistically explain patient heterogeneity and identify prognostic biomarkers. This is a high-impact, interdisciplinary project bridging
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research potential. Teaching may be required. Qualified candidates are expected to have a background in scientific machine learning, numerical analysis, and dynamical systems. Preference will be given
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(https://www.globischlab.org/research-projects/). The analysis will be included into our EU-network PANCAID (https://pancaid-project.eu) that will lead to interdisciplinary scientific interactions within
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scientific network. Contribute your knowledge, vision, and dedication to create a space where scientific discovery in cancer research is transformed into benefits for human health. The Division of Regulatory
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to work independently and collaboratively We are also looking for the following competences: Programming skills (preferably in Python) Experience with statistical analysis tools or using pressure
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Research Network. We kindly inform you that we will contact only selected candidates. Website for additional job details https://system.erecruiter.pl/FormTemplates/RecruitmentForm.aspx?WebID=9f4989dd2… Work
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networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and algorithmic perspectives on large language models Statistical learning theory and complexity analysis