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research. The ideal candidate will have a strong foundation in Python programming and hands-on experience with deep learning frameworks such as TensorFlow or PyTorch. Applicants with a background in Natural
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Max Planck Institute for Biological Cybernetics, Tübingen | Bingen am Rhein, Rheinland Pfalz | Germany | 25 days ago
, biomedical engineering, computer science, physics, or a related discipline. A strong background in fMRI data analysis (e.g., FSL, FreeSurfer, ANTS) and very good programming skills in Python and Bash on Linux
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animal movement analyses. Geospatial analysis, GIS, and remote sensing. Statistical, ecological, and machine-learning modeling using modern analytical software (e.g., R or Python). Google Earth Engine and
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PhD in Advanced Testing, Modelling, and Simulation of Composite Materials under High Velocity Impact
work. Some experience in modelling of composite materials. Some experience in programming (Python, Fortran, CUDA or similar). Some experience in fluid mechanics and biomechanics. Personal characteristics
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, Statistics, Applied Mathematics, Physics, or a closely related STEM field. Demonstrated experience developing AI and machine learning models for biomedical applications. Strong programming experience in Python
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related discipline; An interest in the impacts of land use; Experience in handling spatial data; Programming experience in Python, and/or R; Proficiency in English; and The ability to work as part of
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programming languages such as Matlab, Python, R or C++. You are a team player who possesses good social, communication and organisational skills. You have a passion for science and the pursuit of knowledge
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deep generative models (VAEs, GANs, diffusion models) or probabilistic modelling is a strong plus. You have good programming skills in Python and experience with a deep learning framework such as PyTorch
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of relevant experience. Must have extensive expertise in computational modeling, including strong coding skills in Python. Strong statistical and mathematics background. Preferred Qualifications Merkin Bridge
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; Experience in handling spatial data; Programming experience in Python, and/or R; Proficiency in English; and The ability to work as part of an interdisciplinary research team. The following qualifications