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, testing, APIs, data pipelines, containerisation, reproducible workflows (e.g. Docker, CI/CD, Nix), and programming in languages such as Python, Go, Rust, or similar. Exposure to data modelling or semantic
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, Earth Sciences, Physics, Engineering, or a related field Strong quantitative and analytical skills as well as programming skills (Python required; experience with seismic data processing is advantageous
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Proficiency in Python and machine learning frameworks such as PyTorch, TensorFlow, or JAX Experience with HPC and GPU-accelerated computing Familiarity with foundation models / LLMs; interest in reproducible
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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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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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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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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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, 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 (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