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Duration 2 years Scholarship Value financial and non-material support Up-to-date information is available on the programme website . Application Papers Application forms and further information
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to domain-specific knowledge and research. All three domains – life & medical sciences, earth sciences, and energy systems/materials – are characterized by the generation of huge heterogeneously structured
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the potential for long-term societal impact. Join us in uncovering the biology of aging and shaping the future of healthy longevity. Training and research within the PhD program is interdisciplinary. Lecture
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, energy systems, or material sciences A Masters degree with a strong academic background in mathematics, computer science, physics, material science, earth science, life science, engineering, or a related
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, computer science or mathematics (or a related field), with a focus on computer vision, image processing, or machine learning Solid mathematical and physics background, distinct analytical skills Very good
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, earth sciences, energy systems, or material sciences University degree (M.Sc. or equivalent) in applied mathematics or in computational engineering science, computer science, simulation science with a
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-of-the-art machine learning and computer vision methods and their applications Your Profile: Excellent Master’s degree in engineering, computer science or mathematics (or a related field), with a focus
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at international conferences and learn about state-of-the-art methods in machine learning, reinforcement learning and computer vision for the life sciences Your Profile: Excellent Master’s degree in engineering
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, computer science, physics, material science, earth science, life science, engineering, or a related field Proficiency in at least one programming language (Python, R, C++, Julia, …) Good analytical skills with a
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Profile: Genuine interest in data science and one or more of its application domains: life and medical sciences, earth sciences, energy systems, or material sciences University degree (M.Sc. or equivalent