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of mRNA or expression libraries lead in vivo studies, including delivery, tissue collection, phenotyping, and downstream analysis integrate and analyse multimodal datasets using Python or R to inform
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For Someone Who • Has a PhD in computational biology, genomics, bioinformatics, microbiology, or a related field. • Is fluent in Python/R and Unix-based workflows. • Has experience with microbial genomics
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T cell biology or cancer immunology, and programming skills (R, Python) for data analysis. Please also read recent manuscripts published in the last two years 2024 Nature: (https://www.nature.com
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molecular biology and genetics techniques. Strong quantitative/analytical skills and proficiency in programming in MATLAB, Python, or R. Track record of first-author original research papers. Strong oral and
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: Proficient in Python. Machine Learning: Strong experience with frameworks like TensorFlow, Keras, or PyTorch. Preferred Skills: Experience with Explainable AI (e.g., SHAP, Integrated Gradients
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cytometry leading to publication in peer-reviewed journals is recommended. Preferred skills include experience with mouse models, bioinformatics skills (R, Python), background in T cell immunology, and a
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Essential criteria are: Doctoral degree in computed tomography, image analysis, or similar Demonstrated experience in programming (e.g., Python, MATLAB) Theoretical knowledge and practical experience in
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in programming, ideally with experience in languages commonly used in computational biology (e.g. Python, C). Experience with HPC, workflow managers (e.g. Snakemake, Nextflow), and containerization
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novel machine-learning methodologies Excellent programming skills in Python and familiarity with modern ML tooling and reproducible research practices Experience training and deploying machine-learning
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of molecular phenotypes, Mendelian Randomization, co-localisation); Experience of statistical or other programming languages to manipulate large-scale datasets – e.g. Python, R; Strong quantitative skills and