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microscopy datasets now capture millions of single-cell images across diverse perturbations, but differences in imaging protocols, marker panels, and cell types limit their integration and reuse. A key
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data at an internationally competitive level. Experience of biostatistics or machine learning approaches Proficiency in a scripting language like R or Python, as well as ability to work efficiently in a
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for the project. Have documented programming experience in R, Python or other common programming languages. Have experience of quantitative analysis, computational modelling, bioinformatics, machine learning
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which must be in advanced courses in one of these areas. Alternatively, you have gained essentially corresponding knowledge in another way. Experience with programming (e.g., Python, MATLAB, C/C
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principles and approaches for managing and sharing different types of research data, as well as being engaged in competence-raising networking within research data management in Sweden. To perform the work
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image reconstruction, inverse problems, signal processing, computational imaging, or cryo-EM data analysis is required. Strong programming skills (e.g., Python, C/C++, or similar) and experience with
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evolution across different genomic regions by developing interpretable and efficient methods in comparative pangenomics, leveraging machine learning methods and statistical analysis (https://cgrlab.github.io
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for The following requirements are mandatory for the role: A university degree in a relevant area Documented experience in Python and/or other relevant programming languages Documented experience from working in
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, seminars and conferences. The work duties will also include teaching and other departmental duties (no more than 20%). The candidate will participate in different research projects with duties such as