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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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related field Solid background in physical optics, experience in interferometry and/or cryogenic optics is an asset Extensive experience with optical design and simulation tools (e.g. Zemax, Code V, FRED
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development, validation, and safe integration of locally hosted LLMs for automated coding of pediatric diagnoses from electronic health records (EHRs), with the goal of enhancing research capabilities and
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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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sustainability (max. 0.5 page) • a list of publications and other research outputs, including datasets, code, etc. • a copy of their PhD certificate Please note that page limitations do not include references
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quantitative skills and comfort with coding, and good analytical thinking You are committed to working in an interdisciplinary team blending climate modelling, geochemical process models, and new geochemical
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disseminated through open-source code and scientific publications. Start: As soon as possible (applications reviewed on a rolling basis) Duration: 6 months (extendable) Job description Apply computational and
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(e.g., qualitative coding, statistics, simulation, ML) Publish results in peer-reviewed venues (conferences/journals) and contribute to paper writing Support lab operations as needed (maintaining
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of people (min 2) who could provide a reference (letter). You do not need to submit a letter at this stage Two key outputs (these could be publications, code, visualisations, etc) Please state explicitly when
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environments that help learners develop deeper conceptual understanding and problem-solving skills. Topics may include multimodal representations of code, intelligent feedback mechanisms, and the cognitive