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with 3D cell culture, organoids or tissue engineering will be considered a strong advantage. Experience with image analysis software (ImageJ/Fiji) and scientific computing tools (Python, R or equivalent
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bacterial genome analysis and comparative genomics. * Skills in bioinformatics applied to genomic data analysis. * Experience in data analysis and visualization, particularly using R and/or Python. * Ability
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Eligibility criteria Selection will be based on the following scientific and technical criteria: • PhD in computational biology, machine learning, bioinformatics or a related field. • Proficiency with Python
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biology, bioinformatics, infectious-disease epidemiology, evolutionary or ecological biology, or a closely related field. Strong programming skills (R, Python, and/or other) Familiarity with version control
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analyze multi-omic data provided by our collaborative partners and interpret the results from a biologically relevant perspective. Planned activities include Python code development, the analysis and
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- 4 Additional Information Eligibility criteria - Evolutionary genomics analyses on large NGS datasets -Knowledge on coding (C ,C++, or java), script writing (python, perl), R software and shell Unix
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) to soft matter or related systems; basic knowledge of scattering data modelling is essential. Data analysis skills and programming experience in Python or MATLAB. Ability to work effectively with multi
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analysis software or programming language (R, Python, Stata). Experience in comparative analysis. Ability to integrate into a project-related work team Ability to interact with academic stakeholders in
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should have a good knowledge of scientific programming (e.g., Python, C, Fortran) and finite-element or finite-difference schemes. It will be an asset if the candidate has prior research experience in
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analysis. - Adapt the team's existing data analysis protocols as needed. Expertise in coding (Python, ImageJ) would be a plus. - Be able to communicate research results, whether within the team