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representation learning. Programming skills (e.g., Python) and experience with deep learning frameworks (e.g. PyTorch) Interest in applications to ecological or biological networks Good analytical and
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Numerical methods Programming skills (Python, MATLAB, or similar) Strong analytical and problem-solving skills. Good written and spoken English. Desirable: Experience with photonic/electromagnetics design
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German Cancer Research Center in the Helmholtz Association (DKFZ) | Oettingen in Bayern, Bayern | Germany | 3 months ago
English Experience with the following is a plus: Single-molecule localization microscopy (SMLM) MATLAB/Python Please apply with your CV, motivational letter, and certificates, as well as contact information
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enthusiast (and realist). You love coding and have proven experience in e.g. Python, Matlab, JAVA, C#. You can present and communicate your ideas with AND without LLMs. You get excited about implementing your
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Integrated Circuit (IC) design and Computer Architecture. You should have solid skills in HDL (Verilog, VHDL) and scripting languages (Python, TCL). You should have experience with commercial EDA tools
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background in at least one of the following: Photonics/Electromagnetics theory, design and simulations Nanoscience Visual neuroscience or opthalmology Programming skills (Python, MATLAB, or similar) Strong
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, optics, electrophysiology, or related fields) Programming experience (Python, MATLAB, C++, or similar) Interest in developing novel biomedical technologies Strong motivation for translational neuroscience
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Python or R • Statistical modelling Applicants without prior AI experience are encouraged to apply, as structured AI/ML training will be provided. Dairy Cattle Welfare | Bioacoustics | Precision Livestock
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environments, such as MATLAB, Python or similar tools, will support your work in the project. Knowledge of Power-to-X, electrolysis, renewable fuels, process integration or energy storage will be advantageous
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as Python, R, or MATLAB. Experience working with marine / environmental observation systems, sensor data, and / or remote sensing. Experience handling large or heterogeneous environmental datasets