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industrial stakeholders, and we have ongoing collaborations with Fujifilm Diosynth, Opentrons, Lonza and Neochromsome. In collaboration with OccamBio Ltd, we aim at designing deep learning models to engineer
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record (EHR) as well as MyChart data, with the opportunity to work on applications of machine learning/deep learning/ Natural Language Processing in novel areas of healthcare. The position is open for a
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ATAC-seq, single-cell RNA-seq, spatial gene expression, and whole-genome sequencing (with long reads) data. The candidate will get the opportunity to explore new analysis methods using deep learning
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implementation of deep learning and computer vision frameworks across a range of research projects. This includes developing and training deep learning models for tasks such as scene understanding, object
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Control engineering (experience with nonlinear systems is a plus) Machine learning and deep learning in context of physical systems Programming skills are required, with Python experience preferred. A good
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science, and applied plant research Example reading: Peleke, F. F., Zumkeller, S. M., Gültas, M., Schmitt, A., & Szymański, J. (2024). Deep learning the cis-regulatory code for gene expression in selected
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water. Clearly identified scientific objectives motivate and guide the design and development of space mission by CESBIO and monitoring tools. Missions: - Data processing, apply and tune deep-learning
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one of the following domains are highly desirable: deep learning models on natural language processing or computer vision, advanced analysis of fMRI using encoding or decoding models, computational
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under the guidance of Prof. Ivan Nourdin. Your role Conduct research in machine learning, deep learning, and probabilistic modeling, with a focus on real-world applications Disseminate research findings
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 22 hours ago
with proven excellence in research who have the vision and interest to contribute to interdisciplinary research on foundations of deep learning, optimization, dynamical systems, and control, with