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Field
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research. Experience applying machine learning and statistical modeling techniques to large biological datasets for biomarker discovery, disease prediction, or host-pathogen investigations. Proficiency in
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written and spoken. Experience with experimental fluid mechanics and computer vision is an advantage. Our offer We offer a stimulating, multidisciplinary research environment within the ETH Domain, with
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outcomes of therapy. The lab is looking for candidates for the following two stipends: • Stipend 1: Computer Vision-Based Analysis of Humans. This PhD candidate will focus on developing new AI/computer
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selection criteria Experience with AI / probabilistic AI / Machine Learning / Reinforcement Learning Experience with numerical optimization and MPC Strong programming skills (Python, C) Personal
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. Qualifications and Expectations Applicants must hold (or be close to completing) a Master’s degree in biomedical engineering, mechanical engineering, robotics, computer vision, applied mathematics, or a related
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Machine Learning for Image Classification. Eligibility You must: We would like you to have: sound knowledge of machine learning, computer vision and image processing strong programming skills. How to apply
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CFD, thermofluids and machine learning. Experience in Python (or another language), machine learning frameworks, or CFD tools such as OpenFOAM is beneficial but not required. Applicants should hold (or
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, robotics, and machine learning. You will work within a multidisciplinary supervisory team spanning engineering, robotics, and computer science, and collaborate with researchers working on real-world
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and Technology (NTNU) for general criteria for the position. Preferred selection criteria Experience with AI / probabilistic AI / Machine Learning / Reinforcement Learning Experience with numerical
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of Engineering), Mike Pound (Computer Vision, Computer Science Department), and Darren Wells (Plant and Crop Biophysics, School of Biosciences). Who we are looking for An enthusiastic, self-motivated, resourceful