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, chromatin profiling, genomics, spatial transcriptomics and single-cell data. Apply statistical, machine learning, and network-based approaches to analyze high-dimensional biological data. Collaborate closely
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programming languages. Experience with DICOM data, medical-image registration, high-performance computing, or GPU-based computation. Familiarity with machine-learning or deep-learning methods for medical-image
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Research Fellow (Software, AI & Autonomous Systems) Required Qualifications PhD in Robotics, Computer Science, Artificial Intelligence, Electrical, Computer Engineering, or related disciplines. Key
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of metabolism, membrane transport, cellular regulation, structural systems biology, machine learning and disease mechanisms. These positions are embedded in the transition from CeMM in Vienna to the newly founded
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theoretical statistics and data science, and is heavily involved in research at the crossing of statistics and machine learning. Modern vessels produce vast amounts of multivariate data streams. The project
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to demonstrate skills on Data Analytics and Machine Learning, in particular on distributed ML. Must have very good programming competence in Python, Java, C/C++ or equivalent Fluent oral and written communication
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Center for Biologics Evaluation and Research (CBER) | Southern Md Facility, Maryland | United States | 1 day ago
are held in zoos, research facilities, venom producing facilities, and by private individuals. Exotic antivenoms are also acquired by US military for treatment of personnel positioned in other nations
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academic institutions to translate research into viable solutions. Job Requirements: Preferably PhD in computer engineering, Computer Science, Electronics Engineering or equivalent. Independent, highly
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of) a PhD in computer music, product/industrial design, human-computer interaction (HCI), disability studies, mechanical engineering, mechatronics, robotics, design engineering or other relevant field
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on future long autonomous navigation techniques. About you a PhD in a relevant field or near completion extensive knowledge of robotic navigation, machine learning or other relevant fields experience working