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, highlighting that current (pre)rehabilitation strategies do not effectively promote physical activity. Nevertheless, sufficient physical activity is essential to optimize surgical recovery and achieve broader
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Architecture Search (NAS) that can automatically design efficient deep learning models optimized for specific embedded hardware platforms. These models will be deployed in resource-constrained, standalone
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career, due attention will be given to maintain an optimal equilibrium between research and teaching. You will take responsibility in management tasks of the Department of Pharmaceutical and
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engineering pipeline to derive actionable insight for cancer immunotherapy. Your work will primarily focus on antibody generation, affinity maturation and sequence optimization for target of interest. You will
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experience into account. You contribute to the optimization and continuous development of the educational programs for which the department is responsible, and you supervise bachelor’s and/or master’s theses
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researched by well-optimized experiments and be assessed on various RF devices, such as GaN transistors. The candidate: should have a MSc degree in Electrical Engineering or equivalent; should be ranked within
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highly motivated PhD researcher with an interest in optimizing distributed ML models for resource-constrained devices. The applicant should: have a master’s degree in Electrical Engineering or