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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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. • Integrate and test autonomy stacks (perception, learning, planning) on physical robots. • Use evolutionary algorithms to optimize both the robot’s body and brain together. • Apply quality-diversity
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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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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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experience with R or Python programming is also very desirable. Experience in one or more of the following is an advantage: finite-sample statistical theory, concentration inequalities, statistical optimality
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autonomous navigation but based on the interests of the PhD fellow there are also opportunities to investigate planning and optimization of sensor placement, human-robot interaction, operation in winter and