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: The design and analysis of computational methods that accelerate AI/ML when applied to large scientific data sets; Energy efficient physics-aware algorithms, capable of distributed learning on high performance
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will work on the following topics, in collaboration with the rest of the team: Develop and apply evolutionary algorithms to jointly optimize both the robot’s morphology and autonomy, and apply quality
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of areas, including AI and machine learning, cloud and mobile computing, computer system and information security, evolutionary computation, computer vision and graphics, and bioinformatics
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to the development and implementation of approaches that interface with living systems through novel materials and algorithms, electric and magnetic fields, ultrasound, optics and targeted radiation, microfluidics
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to the research in NCEI, as described in the Project Description above. Experience with AI methods/algorithms such as evolutionary algorithms, quality-diversity methods, and evolutionary robotics. Experience with
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6 Feb 2026 Job Information Organisation/Company Delft University of Technology (TU Delft) Research Field Computer science » Programming Mathematics » Algorithms Mathematics » Discrete mathematics
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environments like health care and environmental monitoring. This PhD project aims to address these challenges by exploring how evolutionary algorithms and reinforcement learning (RL) techniques can be combined
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of algorithms and models to realistically simulate forest ecosystem dynamics under varying conditions of land use change, forest and land management, climate variability, and other environmental stressors
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environments like health care and environmental monitoring. This PhD project aims to address these challenges by exploring how evolutionary algorithms and reinforcement learning (RL) techniques can be combined
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algorithms, electric and magnetic fields, ultrasound, optics and targeted radiation, microfluidics, controlled force sensing and actuation and related tools for probing and controlling biomolecular systems