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Field
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; machine learning or deep learning; pharmacogenomics; computational biology; drug discovery; network medicine; NLP/large language models; or precision medicine 2. Strong programming skills in Python, R
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and/or Python; experience with Unix/Linux environments and bash is considered an advantage Prior experience in the preprocessing, analysis and interpretation of omics data and a strong interest in
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development (experience in multiple fields are considered beneficial). Familiarity with simulation software and numerical methods and proficiency in programming languages (Rust, Python, MATLAB, C/C
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be advantageous: Experience with scientific expeditions Experience in computer-aided analysis of biological sequence datasets (e.g., with R, Python and Bash/Linux environments) Basic understanding
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(meta-)genomes Experience in the computer-assisted analysis of large biological datasets (e.g., using R, Python, and Bash/Linux environments) Very good written and spoken English skills Ability to work
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experimental data. • Proficiency in scientific programming and data analysis tools (e.g., Python, R, Linux/Unix environments). • Demonstrated track record of publishing scientific results in peer-reviewed
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related field with a strong quantitative focus. Strong programming skills in Python and demonstrated experience with machine deep learning frameworks (for instance, PyTorch or TensorFlow), preferably
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or related fields. Two (2) years experience in data analysis. Experience with relational databases and statistical research, data retrieval, and query e.g. geographic information systems (GIS), Python, Numpy
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power systems, energy conversion, modelling, simulation and programming tools (e.g. MATLAB, Simulink, Python), or related research areas will be considered an advantage. Strong analytical skills, a
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documentation, and draft sections of papers or reports Who We're Looking For Bachelor's or Master's degree in Computer Science, Computational Linguistics, Data Science, or a related field Proficiency in Python