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. Qualifications: • Completed academic university degree (Master level) in mathematics, computer sciences, physics or a related discipline • Knowledge of programming, machine learning methods, mechanistic modelling
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statistical methods to estimate the use, effects, and risks of medications based on secondary data and to estimate the progress as well as the survival of cancer. The unit has extensive statistical expertise
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quantitative image analysis, numerical modeling, and explainable AI (XAI) with state-of-the-art biophysical methods. Using techniques such as traction force microscopy, microfluidics, 3D bioprinting, and
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posts,PHD Thesis Starting date: 30.10.2025 Job description: DESY Foundation models are multi-dataset and multi-task machine learning methods that once pre-trained can be fine-tuned for a large variety of
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institutes as well as a secondment in a private-sector partner of the network. The research topics focus on the development of new physics inspired AI methods for inverse problems, uncertainty estimation and
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twin of sperm motility, and utilize it to develop a separation method. Your tasks will include: Performing computer simulations and matching them to experimental data Very close collaboration with
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Max Planck Institute for the Study of Crime, Security and Law, Freiburg | Freiburg im Breisgau, Baden W rttemberg | Germany | 16 days ago
precisely estimated. The position also offers extensive opportunities to liaise with governmental and societal actors in the field of IT security in Germany. The project's findings may lead to improved law
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for the accurate calculation of materials properties. You will combine methods from quantum informatics and solid-state physics to describe the complex electronic and ionic processes in battery materials. New
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-Euclidean spaces Scalable layout methods and visual analytics for large and dynamic networks Dimensionality reduction and embeddings for visual exploration Interaction design and user-centered evaluation
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and digitization. More than 400 employees – including around 100 students – from over 50 countries work at nine locations in scientific and non-scientific teams on the development of innovative methods