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Field
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Python is required. Programming in C or C++ is a plus. Background in statistical genomics, longitudinal modeling, non-parametric statistics, machine learning and deep learning are preferred and encouraged
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learning, at the intersection of reinforcement learning, deep learning and computer vision, in order to train effective robotic agents in simulation. You should hold a relevant PhD/DPhil (or near completion
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Department of Maritime & Transport Technology at Delft University of Technology. Together, we aim to develop sustainable fishing techniques grounded in a deep understanding of flatfish escape behavior and
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upon future funding. Qualifications Required Education and Experience Appropriate PhD in a related field. Preferred Qualifications Experience with machine learning and deep neural network techniques
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the intersection of machine learning and genomics. The project involves the development and application of advanced machine learning and deep learning techniques to understand the sequence-function relationships
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(multiomics), CRISPR genome editing, deep learning, network modeling, confocal and two-photon live imaging. Please visit the Özel Lab Website for more information. Ideal candidates will be highly motivated and
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cooperation with Wageningen Marine Research and the Department of Maritime & Transport Technology at Delft University of Technology. Together, we aim to develop sustainable fishing techniques grounded in a deep
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, debate, discovery and innovation, and our deep commitment to contributing to a better world. Every member of the UC Berkeley community has a role in sustaining a safe, caring and humane environment in
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bioinformatic workflows. Familiarity with biomedical ontologies and text mining on Electronic Health Records and biomedical literature Knowledge of machine learning / deep learning with an interest in
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methods, stochastic control processes, dynamic programming, deep reinforcement learning. Strong track record in scientific contributions supported by peer-reviewed publications. Strong programming skills