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, protein purification, and/or machine learning is a clear plus. • Experience in data analysis and coding (preferably Python) • A systematic, independent working style and ability to work in a collaborative
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, mathematics, physics, engineering, computational biology or a related quantitative field ● Hands-on experience with biological data ● Strong Python skills and experience with PyTorch or JAX, together
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nearby For the Web Data, NLP & LLM profile, you have experience with Python, web scraping, and SQL. Experience with NLP, statistical methods, LLM pipelines, LLM APIs, and/or Docker is a plus For the
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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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(fluid dynamics) is highly beneficial Experience with statistical analysis, coding (R or Python), and digital modelling strongly preferred Willingness to travel (minimum to UK for experimental work
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. Main duties and responsibilities Extract and harden a scoring engine from an existing Python/Streamlit prototype into robust, standalone code Rebuild the data layer from Neo4j to a Python-native graph
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, or layered materials, as well as Python programming (or similar) is a plus. Most importantly, an applicant should be driven by curiosity and should be motivated to work through a difficult long-term (4 years
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surface science Prior experience with piezoelectric- or ferroelectric nitrides is an advantage Knowledge of PVD process development and pulsed sputtering is an advantage Proficiency in Python programming
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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