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Saelens team. Research Project In this research project you will develop probabilistic deep-learning models that automatically extract biological and statistical knowledge from in vivo perturbational omics
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expose the successful candidate to cutting-edge genome editor engineering approaches and the delivery of these reagents in vivo via AAV or lipid nanoparticles. The successful candidate will also learn
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cybersecurity research. Who you are: You have BS in machine learning, cybersecurity, statistics, or related discipline with eight (8) years of experience; OR MS in the same fields with five (5) years
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cybersecurity research. Who you are: You have BS in machine learning, cybersecurity, statistics, or related discipline with eight (8) years of experience; OR MS in the same fields with five (5) years
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etc; Candidates with multidisciplinary backgrounds are welcome. · Strong skills in computational and data analytical methodology development and implementation; experience in machine learning and deep
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& Machine Learning • Clinical pathways and decision support for patients with acute chest pain • AutoPiX – Explainable Deep Learning for Multimodal and Longitudinal Imaging Biomarkers in Arthritis • Speaking
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expected to participate in regular Numata Center programmatic activities. Should you teach, you will be appointed to a lecturer position. Lecturer positions may range up to 33% time. General Duties as a
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for this position, however, we are still accepting applications from other qualified candidates. Position Summary Our goal is to identify computational principles underlying learning and decision-making behavior and
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Saelens team. Research Project In this research project you will develop probabilistic deep-learning models that automatically extract biological and statistical knowledge from in vivo perturbational omics
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University of Massachusetts Medical School | Worcester, Massachusetts | United States | about 1 month ago
modeling, causal inference, or deep learning is a plus Excellent communication skills and enthusiasm for collaborative, interdisciplinary research The Garber Lab is part of a vibrant computational and