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, utilizing cutting-edge reconfigurable computing and sensors. The aim is to develop next-generation electronics and computing solutions that solve technology-related challenges in fields such as autonomous
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mechanism. Recent developments in protein structure prediction and protein de novo design have opened new possibilities for probing such mechanisms. The project will seek to use existing algorithms to new
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implementing inversion algorithms, including a focus on the integration of spatially constrained regularization schemes. Collaborating with forward modeling experts to ensure seamless integration with a recently
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reconfigurable computing and sensors. The aim is to develop next-generation electronics and computing solutions that solve technology-related challenges in fields such as autonomous robots, drones, IoT, smart grid
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programming Creating their own mechanical designs, implement and test them accordingly, Implementation of control algorithms on physical experiments. In addition, the candidates are expected to contribute with
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Examples of research areas that the Associate/Tenure Track Assistant Professor might cover: Leadership for societal transformation and systems change Leadership and algorithms Business leadership and
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based on both visual and tactile information. The candidate will be responsible for developing detailed simulation models of both robots, sensors, and components to be assembled. In addition
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administrative documents as well as to understand spoken everyday Danish. Contacts Rikke Holm Bramsen, Head of Department, email: rholmb@health.sdu.dk , tel. +45 65 50 72 51 Prof. Søren Krogh Andersen, Head of
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learning techniques, as well as methodological issues related to AI (e.g. the fairness and transparency of algorithms) Energy, Environment and Resources Firm Behavior, Innovation and the Functioning