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) on physical robots. • Use evolutionary algorithms to optimize both the robot’s body and brain together. • Apply quality-diversity methods to discover a wide range of high-performing designs
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and iteratively improved. • Integrate and test autonomy stacks (perception, learning, planning) on physical robots. • Use evolutionary algorithms to optimize both the robot’s body and brain
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desirable. Experience in one or more of the following is an advantage: finite-sample statistical theory, concentration inequalities, statistical optimality theory, sequential inference, computational
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, CRISPR technology, chemical screening platforms, and precision oncology. Responsibilities Develop and optimize in vitro models and methodologies to investigate cytotoxic lymphocyte-mediated cancer cell
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, concentration inequalities, statistical optimality theory, sequential inference, computational complexity theory. Language requirement: English requirements for applicants from outside of EU/ EEA countries and
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opportunities to investigate planning and optimization of sensor placement, human-robot interaction, operation in winter and arctic conditions, as well as use of communication nodes in addition to the sensor
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-healing functionalities embedded for battery longevity with manufacturability and economical recyclability) funded by the European Commission. The candidate will focus on: Electrode development Optimization
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narrative teaching portfolio outlining prior teaching experience and pedagogic qualifications (max 3 pages; optimally organized around the four principles of Scholarship of Teaching and Learning in Higher
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pedagogic qualifications (max 3 pages; optimally organized around the four principles of Scholarship of Teaching and Learning in Higher Education). List of 2-3 reference persons (name, relation to candidate
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program though the Research Council of Norway. The candidate will focus on development of solid-state electrolytes, optimization of materials using ALD, electrochemical evaluation and operando