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simulation and enhanced sampling techniques. Candidates must be proficient in Python and familiar with version control platforms such as GitHub. You should demonstrate a strong research track record through
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modelling; strong programming and research engineering ability (Python with modern ML tooling such as PyTorch/JAX) and good software practices; familiarity with interactive/agentic settings (e.g., tool-using
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imaging data, preferably using Python, and hands-on experience building bespoke laboratory setups for imaging experiments investigating alloy composition or relevant applications. You will have a strong
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the programming languages Python and R, and with the writing of bioinformatics and AI / ML analysis pipelines for spatial transcriptomics / proteomics data and/or single-cell genomics data . You will be highly
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scientific results clearly within a multidisciplinary research team. Experience working at containment level 2/3, with hard X-ray nanoprobe technology, or with data analysis tools such as R, Python, FIJI
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and Edge Computing Good programming skills (e.g., Python, MATLAB, C++) and experience with system simulation. Experience with industrial field projects or familiarity with DCS/MES systems is preferred
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skills in R and/or Python and experience in statistical modelling of high-dimensional biological data. Experience working in HPC environments and managing large-scale sequencing datasets is essential
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their evolution and spatial spread? This post is full time and fixed-term for 12 months. Prior work on the topic from our team is available at: https://www.pnas.org/doi/10.1073/pnas.2412424121 https
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sensing. are essential as well as strong computing skills, including the knowledge of UNIX/Linux, Fortran, Python, or other high-level languages. The post is full time and fixed term for 18 months
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of economics and experience in data management and analysis. You have demonstrable experience of working with quantitative data and relevant software (Stata, R, Python, or similar). This is a full-time, fixed