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Future robots must perceive, predict, communicate, and decide reliably in complex, human–robot shared environments. The Mobile Robotics ( https://www.aalto.fi/en/department-of-electrical-engineering
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, and decide reliably in complex, human–robot shared environments. The Mobile Robotics ( https://www.aalto.fi/en/department-of-electrical-engineering-and-automation/mobile-robotics ) and Intelligent
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ignore known biology and provide limited insight into uncertainty and mechanisms. These challenges motivate a broader Biology-Informed Machine Learning perspective [1]. The doctoral student’s thesis
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and conditions, and some relevant biological states are unobserved. Purely data-driven models offer flexibility, but often ignore known biology and provide limited insight into uncertainty and
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. Familiarity with uncertainty modelling, stochastic programming, robust optimization, or real-time decision-making. Interest in quantum computing or quantum-inspired optimization methods. Good programming skills