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that prioritise student learning in the age of AI. Job requirements You hold a PhD in Educational Science, Learning Sciences, Social and Behavioural Sciences, Engineering Education, Human-Computer Interaction or a
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As a postdoctoral researcher, your primary responsibilities will be: Develop machine learning and deep learning models, with a strong focus on computer vision, for the characterisation and
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scientists. You meet the following criteria: • a PhD, or a PhD close to completion, in machine learning, artificial intelligence, computational biology, bioinformatics, computer science or a closely related
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researcher who enjoys developing methods for complex biological data and working closely with experimental scientists. You meet the following criteria: a PhD, or a PhD close to completion, in machine learning
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requirements For this postdoctoral role, we are looking for someone with a demonstrated background in SAR processing, SAR applications in agriculture and machine learning: A PhD in Earth Observation, Geodesy
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the pragmatism that is needed to move a project forward. By the time the position starts, you have obtained a PhD degree in Data Sciences, Computer Sciences, Physics, Earth Sciences, Civil Engineering, or a
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, troubleshoot and improve the setup and ensuing workflows. You have a PhD degree in chemical engineering, physical chemistry, materials science, or a closely related field. You have hands-on experience with
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for support in technology development. You will work closely with a PhD researcher at the German partner who focuses on the underlying machine learning models, and you will help coordinate the joint work across
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across a range of application areas, including education and healthcare. As these systems are increasingly deployed in high-stakes environments, there is a growing need for machine learning models
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requirements We will consider applications based on the following skillsets. If you do not fullfil all requirements, please still apply (there is room for learning-on-the-job). A PhD in aerospace/mechanical