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, Computational Biology, Statistics, Computer Science, Artificial Intelligence, Physics, Engineering, Bio-engineering, or equivalent. Proven track record of successful research and high-ranked publications in
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trajectories. Leveraging deep learning, generative models and cross-modal autoencoders and working with both structured and unstructured data, the goal of this project is to develop a statistical framework and a
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on joint initiatives. Your Profile Bachelor or Master's degree in Bioinformatics, Computational Biology, Statistics, or Computer Science High competency in R and/or Python Solid grasp of statistics Excellent
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, Statistics, Computer Science, Genetics, or equivalent. Proficiency in Python and/or R, with a solid grasp of statistics. Excellent organizational and time management skills, with a flexible mindset for
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. Profile Essential Requirements Masters in Bioinformatics, Computational Biology, Statistics, Computer Science, Genetics or equivalent, but a PhD degree is certainly a plus Detailed knowledge in Python and
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a quantitative discipline (e.g., Physics, Computer Science, Mathematics, Machine Learning, Statistics, Bioinformatics, Computational Neuroscience). You have a genuine interest in interdisciplinary
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, Computer Science, Mathematics, Machine Learning, Statistics, Bioinformatics, Computational Neuroscience). You have a genuine interest in interdisciplinary work at the interface between machine learning and
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doctoral thesis after 4 years Desirable but not required Experience with yeast molecular biology (PCR, transformation, large-scale assays) Knowledge of statistics packages and/or data analysis using R Key
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data integration basic/intermediate programming skills in R and/or Python Ability to adapt to the research environments while being full members of two labs Desirable skills statistical analysis basic