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skills. Experience with programming, preferably Python and R, is required. Experience with mass spectrometry data, in particular metabolomics, and geometric machine learning is a plus. In addition to above
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skills. Experience with programming, preferably Python and R, is required. Experience with deep learning frameworks, such as JAX or PyTorch, is a plus. In addition to above-average interest in the topic
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programming language (preferably Python) What we offer: A fully funded 75% doctoral position (TV-L E13) for up to 36 months • A competitive salary based on TV-L E13 for Bavaria • Enrollment as a doctoral
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systems and basic knowledge in information theory ▪ Proficiency in at least one programming language (e.g. Python) ▪ Interest in AI‑based attack models and security research The following points
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a related field ▪ Strong knowledge in wireless communication systems, signal processing, or radar systems ▪ Proficiency in at least one programming language (e.g. Python) ▪ Interest in hands
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, modelling and simulation in CFD/FEA. Experience with scientific programming (at least Python and C++). Excellent written and spoken English. Very strong team working skills in international, interdisciplinary
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: TUEILSY-PHD20240930-SAS) Safe Collaborative Manipulation in Cluttered and Dynamic Environments (ID: TUEILSY-PHD20240930-SCMM) A more detailed topic description can be found at https://www.ce.cit.tum.de/lsy
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Requirements: Applicants should hold an MSc or Diploma in Engineering, Computer Science or a related discipline. Background in Machine Learning and Artificial Intelligence. Strong programming skills (Python
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RNA sequencing workflows and basic bioinformatics • Experience with Python and R for transcriptomic data analysis We offer The position (TV-L13 (65%) salary according to German public sector regulations
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academic performance. Experience with stochastic methods, risk and reliability analysis, and data analysis. Programming experience in Python, MATLAB, C/C++, or a similar language. Strong analytical