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Field
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contributions will directly influence next-generation robotic systems, from surgical robots requiring precise manipulation to manufacturing systems handling delicate objects such as fruits. Working
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. The main objective is to maximise the scientific return of the missions for the benefit of humankind. The Science Engagement and Oversight Office and the Science and Operations Department also support
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applying and developing deep learning models (e.g. CNNs, ViTs, or geometric deep learning) Proficiency in Python and PyTorch Motivation to work with interdisciplinary clinical partners A track record of
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, MENA, or Central Asia region—in line with the objectives of the funded project and in close collaboration with the Principal Investigator. Collaborate closely with the Principal Investigator on the team
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and machine learning for industrial image analysis (in thesemiconductor industry), B) Automatic geometric vessel tree tracking and analysis in medical image analysis applications, Assist in
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difficult and the creation of more intelligent process control strategies and innovative methods of tracking reliability can be achieved with expert informed machine learning techniques, which offer more
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: Data management and programming (e.g., Python) Life Cycle Assessment (LCA) Multiple Criteria Decision Analysis (MCDA) Multiple Objective Optimization (MOO) In case you do not have all the desired
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Criteria Decision Analysis (MCDA) Multiple Objective Optimization (MOO) In case you do not have all the desired expertise, you demonstrate strong motivation to develop yourself in those areas. You have
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Criteria Decision Analysis (MCDA) Multiple Objective Optimization (MOO) In case you do not have all the desired expertise, you demonstrate strong motivation to develop yourself in those areas. You have
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/optimization is an advantage. Track record of scientific publications in relevant fields (thermal systems, solar energy, PV/T, energy in buildings). Ability to work independently and in a team, with strong