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available single-cell sequencing data generated from patient samples and mouse models, we will enhance and apply machine-learning based algorithms to deconvolute bulk tumor RNA-seq samples to distinct immune
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the controlled flow at tunable temperature and photopolymerization of the precursor. The practical work will be complemented by fluid mechanics computer simulations, including solutions employing machine learning
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in image processing, quantitative analysis, and biological interpretation Proficiency in AI/machine learning tools for image segmentation, transformation, registration, or tracking Solid mathematical
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Senior Scientist / Group Leader on Bioinformatics / Computational Biology on RNA Regulation in Disea
studies Apply machine learning to uncover novel mechanisms and therapeutic insights Mentor junior scientists, contribute to grant writing and publications, and drive the lab’s scientific vision Apply
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, or machine learning applications in health. The successful applicant will establish and lead an independent research group that complements the institute’s mission to advance personalized approaches
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projects and technical leadership. Basic Qualifications: Master's degree or PhD in Computer Science, Artificial Intelligence, Machine Learning, Statistics, or a related technical field. Proven experience in
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often related to domesticated species and humans, but increasingly also on other organisms. Our focus areas include quantitative genetics, deep learning, machine learning, population genetics, integrative
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the broad landscape of computational science, including artificial intelligence, machine learning, deep learning, and their applications in addressing complex scientific and societal challenges, encompassing
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(data assimilation, machine learning, etc.) Writing proposals / securing external research funding Writing and submitting scientific papers Leading a research group Supervising students Participating in
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techno-economic assessments is preferred, and knowledge of applied computational techniques and machine learning methods is a plus. Postdoctoral research experience is preferred but not essential. A