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language models (LLMs) Proficiency in Python programming and confident use of Unix/Linux environments; ideally experience with version control systems (e.g., Git) Interest in or experience with semantic web
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the application of machine learning (ML) methods or large language models (LLMs) Proficiency in Python programming and confident use of Unix/Linux environments; ideally experience with version control systems (e.g
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the pheromonal communication between and within the sexes. Read more about the project here We seek a motivated candidate who can work both independently and as part of a multidisciplinary team. Requirements: A
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-based Max Planck Institutes and Universities with English as the main language Individual supervision and mentoring by world-leading scientists Paid PhD positions and full funding for international and
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network of passionate young scientists in Munich. WHAT DO WE OFFER? A structured PhD program created by Munich-based Max Planck Institutes and Universities with English as the main language Individual
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evaluated. • Ability to convey practical and theoretical knowledge in a didactically suitable form. • Good teamwork and communication skills, as well as a sense of professionalism and responsibility
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of biochemistry, structural biology, biophysics, cell biology, systems biology, and computational biology. Our community IMPRS-ML brings together two renowned Max Planck Institutes, the Max Planck Institute
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Financing yes Type of Position Full PhD Working Language German Required Degree Magister (Masters degree course) Master Areas of study Sociology, Social Science, Economics Description Description As part of
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, modelling and simulation of photonic systems, sensor systems, signal processing and device manufacturing, development of machine learning algorithms, and design of optical communication networks or power
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sciences such as biology, biochemistry, pharmacy or equivalent Language skills (according to GER): English – C1 The successful candidate will also be expected to: Enthusiasm for science and interdisciplinary