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focuses on advanced methodologies in abdominal imaging, particularly applications of machine learning and deep learning to medical image analysis. The lab aims to advance existing imaging techniques and
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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
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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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in ML research. Demonstrated ability to work on the interdisciplinary team. Strong programming skills and familiarity with deep learning libraries. Empty heading Preferred Knowledge, Skills, and
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University of Massachusetts Medical School | Worcester, Massachusetts | United States | about 2 months ago
nanoparticles. The successful candidate will also learn cutting edge deep-sequencing approaches to evaluate off-target editing within the genome. They will have the opportunity to participate in meetings
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electromagnetic device performance analysis>>>Embedded SystemsResearch focuses on:•Robotics, computer vision, and machine learning/deep learning•Wearable and implantable sensors, biosensors, and tele
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deep learning and scalable deployment Collaborate with researchers, developers, and traders to improve existing models and explore new algorithmic approaches Design and run experiments using the latest
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impact, leveraging one of the highest-quality financial datasets in the industry. What You’ll Do Conduct research and develop ML models to enhance trading strategies, with a focus on deep learning and
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complete) an M.Sc. (or equivalent) in Computer Science or a related discipline ML expertise: You have strong programming and deep learning experience (e.g., PyTorch, TensorFlow), backed by a substantial
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unique atmosphere where there is expertise to dig deep into computational modelling, while remaining connected to the experimental side. This interdisciplinary atmosphere has been a main catalyst for many