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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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and skilled individual to join our cross-disciplinary research team studying the ecology of vision. Our goal is to better understand the inter-relationships between vision, evolutionary processes
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biology, genetics, aquatic biology, toxicology, ecology, and evolutionary biology. The Department also operates Finse research station, the Biological research station in Drøbak and UiO's research vessel
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network Research Fields: Hormones, Digital Health, Medical Sensors, Physiology Secondments: University of Ulm (Germany): Algorithms for wearable data analysis University of Manchester (UK): Mathematical
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Medicine Secondments: University of Ulm (D): To work with algorithms for wearable data University of Manchester (UK): To learn mathematical modelling of hormone rhythms. University of Bristol (UK): To learn
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training courses and workshops of the ENDOTRAIN network Research Fields: Hormones, Digital Health, Medical Sensors, Physiology Secondments: University of Ulm (Germany): Algorithms for wearable data analysis
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(D): To work with algorithms for wearable data University of Manchester (UK): To learn mathematical modelling of hormone rhythms. University of Bristol (UK): To learn mathematical modelling of hormone
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. The primary objective of SURE-AI is to create a new generation of algorithms for inference and decision-making by pushing the boundaries of computational techniques. The research emphasizes efficiency in
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the department is organised in five sections covering topics within biochemistry, molecular biology, physiology, cell biology, genetics, aquatic biology, toxicology, ecology, and evolutionary biology. The