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Field
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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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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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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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knowledge in the field of bioinformatic genome analysis Solid programming skills in Python and Bash (without the use of AI) Experience in stand-alone software development Excellent English language skills
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learning, statistical modeling, and modern AI methodologies Strong programming skills, preferably in Python and common data analysis frameworks Experience in designing, conducting, and documenting data
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is desirable. Basic understanding of embedded systems and processor architectures. Strong programming skills (C/C++, Python; hardware description languages such as HLS or VHDL are an advantage
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of LLMs is desirable. Basic understanding of embedded systems. Familiarity with fault detection, system reliability, or troubleshooting techniques. Strong programming skills (C/C++, Python; hardware
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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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algorithms are desirable. Strong programming skills (C/C++, Python; hardware-description languages “e.g., HLS, VHDL” is a plus). Motivation to pursue a PhD and contribute to applied AI research. Excellent
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curATime (Cluster for Atherothrombosis and Individualized Medicine ; https://curatime.org/ ) a Clusters4Future initiative funded by the German Federal Ministry of Research, Technology and Space (BMFTR