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As a Software Developer at the SciLifeLab Data Centre, you will develop and maintain national systems for research data, using Python and Kubernetes to build scalable and sustainable solutions. Join
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at undergraduate and master’s levels, primarily in data science, machine learning, and AI programming in Python, including lecturing, supervision of student projects, course development and examination. Scholarly
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scheduling systems. Basic programming skills in Python are required, as well as experience working with biological or biomedical datasets. The successful applicant should demonstrate the ability to work both
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, including time series analysis and statistics (e.g. mixed effects modelling) Capacity to develop computer code and experience with programming languages (Matlab, Python, R) and geospatial tools (e.g. ArcGIS
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of experience in training, evaluating, and deploying machine learning models, including deep neural networks and relevant frameworks - Documented several years of experience in systems development with Python and
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, neuroscience, electrical engineering, or a related field, hands-on experience with neural recording and/or stimulation techniques, signal processing, and data analysis (e.g., MATLAB or Python), experience
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, Applied Physics, Nanotechnology, or equivalent. Strong programming skills in high-level languages, specifically Python. Good verbal and written communication skills in English. A collaborative attitude and
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. Our software is built primarily in Rust, with R and Python parts to support bioinformaticians. Our web frontend is also developed in Rust (web assembly) – all to support fast computing and handling
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for seeking the position. Extensive experience with Python, Matlab, and R, and good UNIX knowledge are essential skills, as well as familiarity with biological omics data analysis techniques. Experience with
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, contributing to the development and maintenance of FlaGs and its web server for comparative genome analysis, developing Python-based tools and code for retrieval and processing of publicly available genomic data