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Field
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FieldComputer scienceEducation LevelMaster Degree or equivalent Skills/Qualifications Strong foundations in Machine Learning and Deep Learning Excellent Python programming skills Experience with PyTorch
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The Cluster of Excellence Physics of Life" (PoL, https://physics-of-life.tu-dresden.de/en ) is an interdisciplinary research center at TUD Dresden University of Technology dedicated to quantitative
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diversity methods, data management, reproducible code, R/Tidyverse, machine learning and AI for ecologists, visualisation, evidence-based policymaking, science-policy communication, and policy brief writing
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or car 30 days of vacation Participation in the benefits program for employees („Corporate Benefits“) The advertised positions are available for initially 3 years. We promote the employment of people
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of machine learning and clinical oncology, with access to a large multimodal research dataset, substantial GPU resources, and a collaborative scientific environment. Your tasks Design and implement LLM-based
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University of Tübingen − Faculty of Medicine | Baden Baden, Baden W rttemberg | Germany | 3 months ago
therapeutic targets, primarily in T cells, ideally through functional genetic screens in T cells and CAR T cells. In addition to the use of CRISPR/Cas9 technology, the development of further innovative
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sustainable operation of future energy networks by combining our knowledge of energy systems with cutting-edge developments in machine learning, generative AI, and digital infrastructures. Your Job
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Faculty of Medicine of the University of Cologne | German Cancer Research Center (DKFZ) | Gronau Westfalen, Nordrhein Westfalen | Germany | 3 months ago
appointment according to the “Jülicher Modell”). The chair will be newly established at the NCT West, Campus Cologne (https://nct.dkfz.de/standorte/nct-west.html ). The NCT is a long-term collaboration between
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put emphasis on methods of distributed computing, machine learning, image and text analysis, randomized data structures, high-performance computing, and quantum algorithms. Beyond this research, we aim
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, organization, compression, analysis, and visualization of georeferenced or geometric data on large scales. We put emphasis on methods of distributed computing, machine learning, image and text analysis