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, SGLang, PyTorch internals, or similar) Interactive theorem proving (Rocq, Lean, HOL, Isabelle, or similar) or other formal methods Experience maintaining development tooling: build systems, continuous
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the expertise, methods, and software to enhance privacy, data protection, and transparency; notably by the use of cryptography, blockchains and smart contracts, machine learning, software verification, device and
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innovation (in particular, compile the EPFL inputs to the energy statistics for the Swiss Federal Office of Energy). Profile Phd Degree in a field relevant to energy Professional experience in a business or
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discovery through public and Novartis-internal datasets. We are looking for candidates with A PhD in machine learning, computer science, computational biology, or a closely related field (completed or near
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work, as well as record and report results with clarity and details. Proactive and motivated to learn and master new methods and techniques. Able to work independently and within a team. We offer
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. Profile Essential: PhD or equivalent advanced degree in life sciences, biomedical sciences, genetics, bioinformatics, public health, or a related field. Significant experience managing human biological
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to learn new methods and troubleshoot technical challenges Excellent written and spoken English communication skills We offer A dynamic and multicultural working environment within an internationally
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Master's degree or PhD in science, engineering, business administration, or a related field. Proven experience in strategic planning, business development, innovation management, or the setup of research
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lab team to investigate novel material formulations, fabrication approaches, and characterisation methods to develop materials with tailored functional properties. The research will focus
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asset for interacting with EPFL's administration Reliable, proactive, and comfortable working directly with faculty, PhD students, and undergraduate TAs What We Offer A role at the operational heart