88 programming-"https:"-"https:"-"https:"-"BioData" positions at ETH Zurich in Switzerland
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responsibilities with the ECAF faculty Director, overseeing and coordinating technical staff and student assistants. Maintenance and service coordination: Plan and coordinate preventive maintenance, servicing
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for the renewable energy sector via the M2A European Training Network (ETN), funded by the European Commission’s Horizon 2020 Marie Skłodowska-Curie programme. Project background M2A puts forward a robust methodology
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-learning models on distributed systems Strong programming skills in Python and familiarity with a modern ML stack (e.g., PyTorch, hydra, zarr, dask) and best practices MLOps Experience in handling and
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. Strong programming skills in Python and familiarity with a modern ML stack (e.g., PyTorch, hydra, zarr, dask) Experience in handling and processing large datasets or experience in high-performance
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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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scientific publication. Source Data extraction from PDF documents to compile metadata of projects funded under ETH Board Open Research Data (ORD) program Contribute to data packages generated by openwashdata
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of Competence in Research (NCCR) Separations. Job description Within a broader research program that integrates process modelling, computational materials screening and discovery, experimental synthesis, and
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articles, not programming). This position offers an excellent opportunity to learn basic methods of meta-analysis, get an overview of an educational field that is of growing interest, and gain quantitative
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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