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for emulating constrained optimization problems Advanced programming skills in Python, with deep experience in libraries such as PyTorch, Pyomo, and the broader scientific stack (Xarray, Pandas). Knowledge
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. Required PhD in Computer Science / AI / Machine Learning Strong publication record in AI, ML systems, or related areas Strong programming skills in Python, C/C++ and experience with PyTorch, TensorFlow, JAX
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or Master's level) Interest in geophysics, civil engineering, or data-driven infrastructure monitoring Practical, hands-on attitude for field and laboratory work Programming experience (Python preferred
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, ASAP, or equivalent) Programming skills in Python, MATLAB, or similar Ability to work independently as well as in interdisciplinary teams Very good command of English (written and spoken) Preferred
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programming skills in Python Experience with machine learning systems or LLM-based architectures Experience working with complex data systems or developing applied AI prototypes Familiarity with modern AI tools
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- or nanoplastics, online or offline ice nucleation experiments. A good knowledge of programming languages such as Python, R, MATLAB or IGOR is expected. Excellent English skills, both in verbal and written
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related field Strong Python programming skills and experience with PyTorch or TensorFlow Interest in multimodal data, time-series analysis, or NLP Excellent English; German or French is an asset
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programming skills (ideally Python) and commitment to clear, reproducible, well-structured code Working knowledge of SQL and/or NoSQL databases (and motivation to deepen your expertise) Strong analytical
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) Requirements: Experience with analyzing GPS tracks Good data-handling skills and ability to use R (compulsary) and preferably also Python and/or GIS competently Statistical/causal inference knowledge PhD degree
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Computer Science, Biomedical Engineering, Data Science, Cognitive Science, or a related field Strong Python programming skills and experience with PyTorch or TensorFlow Interest in multimodal data, time-series