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or application of machine learning/optimization methods Have good English communication skills An exceptional candidate may optionally have one or more of the following experiences: Experience in analyzing spatial
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for reward funds such as voluntary carbon markets, offset markets, or tax clubs (e.g. on aviation, maritime shipping, or luxury goods). Use of empirical or machine-learning techniques for estimating baseline
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motivated PhD students, interns, and PostDocs at the intersection of computer vision and machine learning. The positions are fully-funded with payments and benefits according to German public service
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success rates of real, patient-specific aneurysms, their treatment options, and long-term prognosis. The project is complemented by contributions in machine learning, such as the rapid generation
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areas, notably in Physics-Enhanced Machine Learning, Computer Vision & AI, and AI in Health Care and Medicine.The position is a full-time position (100%), initially for 2 years and 3 months, with
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colon. The project is funded through the ERC "Unstable Genome". The position is co-supervised by Wolfgang Huber at EMBL and Dr. Aurélie Ernst at DKFZ. The Huber group develops statistical and machine
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on the design and evaluation of innovative data- and machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization
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on the design and evaluation of innovative data- and machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization
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(e.g. via machine learning) to qualitative analyses (e.g. via interviews) to support ambitious policies for climate and energy transitions. This position Green hydrogen is key to decarbonizing many hard
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research, teaching and knowledge transfer to society on artificial intelligence, machine learning, data-centered engineering and related data and knowledge-based technologies, with special dedication