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algorithms and deep learning models. Have proficiency in Python in a Linux environment and development experience using Tensorflow or PyTorch. Have strong linear algebra and computer vision knowledge. Have
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of tissue plasticities in diet-induced obesity and regression. For the current project Unlocking the Deep GPCRome for Accelerated Fibrosis Resolution we seek a molecular and cell biologist or similar with
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learning, deep learning and relevant software framework (R and Python) is highly desired. Very good oral and written communication skills in English are required. Emphasis will also be given on personal
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part-time position with a weekly working time of 30 hours per week (75%). The PhD position is funded by Deutsche Forschungsgemeinschaft (DFG) and related to the major multi-national initiative “Deep Dust
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affordable for parents and nurseries. Training: Data Deep Dive: You'll analyse data from interviews/focus groups/questionnaires with nursery staff, parents, and health protection teams, uncovering social and
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uncovering the deep evolutionary roots of human health and disease. Application Procedure At Trinity, we are committed to equality, diversity, and inclusion. Trinity welcomes applications from all individuals
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relevant experience in the development and deployment of machine/deep learning models as well as the use of remote sensing data You must have relevant experience in the development of hydrodynamic and water
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cybersecurity research. Who you are: You have BS in machine learning, cybersecurity, statistics, or related discipline with ten (10) years of experience; OR MS in the same fields with eight (8) years
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data analysis, programming, and biology. You will be part of a collaborative research team with deep experimental and analytical expertise, with access to advanced tumor models and state-of-the-art
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work schedules tailored to your needs as well as remote work are key parts of our work culture. An exciting and varied job where you will gain deep insights into a research institute as well as national