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(specifically machine learning) in early drug discovery, precision medicine and clinical trials. The team is internationally well connected and is working closely together with leading European and US
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(specifically machine learning) in early drug discovery, precision medicine and clinical trials. The team is internationally well connected and is working closely together with leading European and US
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by Prof. Marcel Oliver, is part of the Mathematical Institute for Machine Learning and Data Science (MIDS) at the KU Eichstätt-Ingolstadt. The research group works at the intersection of analysis
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fine-tune machine learning and deep learning models to extract meaningful patterns and predict metastatic behavior Collaborate closely with experimentalists for mechanistic dissection of multimodal
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Helmholtz-Zentrum für Infektionsforschung GmbH | Braunschweig, Niedersachsen | Germany | about 1 month ago
: Experience programming in Python, Julia, or C/C++ Experience with Mathematica Experience with finite element methods, agent-based simulations, and/or machine learning LanguagesENGLISHLevelExcellent
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D modelling Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country Germany Application Deadline 22 Oct 2025 - 00:00 (Europe/Brussels) Type of Contract Temporary Job Status Full
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Your Job: In this position, you will be an active part of our AI Consulting Team. Together with our partners, we develop new and innovative applications of Machine Learning. You will connect
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Max Planck Institute for the Structure and Dynamics of Matter, Hamburg | Hamburg, Hamburg | Germany | 2 months ago
, i.e. the green transition, with the ultimate goal of reaching climate neutrality by 2050. By leveraging characterisation, multiscale modelling, machine learning, and numerical optimisation, the project
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of the project InsAIderKnowledge funded by the Georg-Nemetschek-Institute for the duration of 48 Months. The candidate has the opportunity to pursue a doctoral degree (PhD). Renumeration is 100% TVL E13 according
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, conservation genomics, museomics, metagenomics, annotation, machine learning, Instruct users in the usage of hardware and software for molecular biodiversity research, Acquire substantial third-party funding