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Swiss Federal Institute for Forest, Snow and Landscape Research WSL | Switzerland | about 2 hours ago
degree in hydrology, environmental sciences, climate sciences, or a closely related field. We seek candidates with strong skills in programming (e.g. R or Python), statistics, risk assessments, and data
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comprehensive and innovative methods to directly test palaeoecological hypotheses using both fluid dynamics simulations and experiments, which will be applicable across the study of life on Earth. https
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methods Master’s degree in Mechanical Engineering or a related field Motivated to conduct internationally leading research Strong programming skills in Python English is the main working language German is
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engineering ability (e.g., OCaml, Rust, C/C++, Python, or other functional languages) Strong publication record (relative to your career stage) in internationally leading venues (e.g., POPL, PLDI, ICFP, OOPSLA
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Python Familiarity with digital twins, building information modelling (BIM) and IFC, sensor data processing, or tunnel inspection would be considered an advantage Willingness to carry out field work in
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, preferably in Python, and experience with optimisation solvers Familiarity with infrastructure asset management, Bayesian networks, decision analysis, Value of Information analysis, or business process
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., vLLM, SGLang, or similar inference engines) Strong computational and analytical skills, including solid software engineering ability across multiple languages (e.g., Python, C++, OCaml, functional
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or education deemed equivalent; experience in the field Excellent technical knowledge of systems programming, and strong programming ability in several of: Python, C/C++, Rust, OCaml, or other functional
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experience with piezoelectric- or ferroelectric nitrides is an advantage Knowledge of PVD process development and pulsed sputtering is an advantage Proficiency in Python programming Interest in lab-automation
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through innovative biomedical research and engineering solutions, translating basic science into medical knowledge and healthcare innovations. The Pediatric Disease Modeling Lab (https://dbe.unibas.ch/en