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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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phosphorus-driven eutrophication, with experience in soil monitoring and erosion processes. Skills in GIS, spatial analysis of large scale data, modelling, remote sensing, and programming (R or Python
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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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mechatronics systems is a plus Excellent coding skills in python, ROS, and RL&IL pipeline experience on simulator and training libraries. Knowledge on C++ is a plus Experience with Physics simulators such as
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Strong programming skills in Python (e.g., PyTorch) Experience with data processing, visualization, and experimentation workflows Knowledge of additive manufacturing processes or industrial monitoring
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related field with experience in water chemistry, silviculture, experimental field work and large-scale data analysis. You must have good statistical skills and programming experience (e.g., in R or Python
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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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chemical research and IT systems. Proficiency in Python (or a comparable scripting language) for data analysis, workflow automation, and process optimization. Working knowledge of Linux and Windows operating
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and/or cognitive neuroscience, preferentially in the field of attention and memory Excellent research methods knowledge and skills Solid programming skills (e.g., MATLAB, R, Python) Demonstrated