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degree in computer science, mechatronics, or electrical engineering. Strong programming skills (C/C++, Python; hardware description languages such as HLS or VHDL are an advantage). Knowledge of computer
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well as experience in omics data analysis, and possesses solid English-language skills. Experience with programming, preferably Python and R, is required. Experience with deep learning frameworks, such as JAX
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problems Proficiency in data analysis and programming using at least one statistical program such as R, Python, or similar programming languages Experience with GAMS, GTAP, and Exiobase is an asset. Skills
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, including SPICE and related tools (LTspice, Cadence, MATLAB, Python) Excellent communication skills and ability to work in a team are essential Strong English skills will be required for the international
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learning pipeline in Python (using e.g. PyTorch) - validation of your results in collaboration with colleagues from various application areas (cross-disciplinary) - publication and presentation of your
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with emerging memory devices Experience with simulation tools (LTspice, Cadence, MATLAB, Python) Interest in brain-inspired computation, energy-efficient hardware, and experimental validation Ability
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, please visit: https://qbm.genzentrum.lmu.de/application/ Tuition fees per semester in EUR None Combined Master's degree / PhD programme No Joint degree / double degree programme No Description/content
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pipeline in Python (using e.g. PyTorch) validation of your results in collaboration with colleagues from various application areas (cross-disciplinary) publication and presentation of your scientific results
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Familiarity with statistics and programming experience in Python are advantageous Strong intention to be a part of international team with interdisciplinary questions We offer: An interesting and vibrant field
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continuum within the 2nd phase of CLICCS (https://www.cliccs.uni-hamburg.de/about-cliccs/cliccs-ll.html). In CLICCS-M4, we are further developing the unique ICON-Coast model within the ICON Earth System