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Optimization (DPO) and reinforcement learning from human feedback, building preference datasets together with clinicians - Build and run a Red Team process with physicians, computer scientists, and patient
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generation of social, computer-based, and cyber-physical systems that make a substantial contribution to the welfare of our society, for example, via embodied intelligent systems that are tailored to users
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with high-dimensional, often noisy, data sets; and mathematical modelling approaches that reduce the dimensionality of parameter spaces and produce mechanistically realistic, experimentally testable
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Analyze dynamical states of spiking complex neuron networks with respect to network topology and neuron parameters Development of learning rules considering the strong non-linearities of the neurons
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parameters Development of learning rules considering the strong non-linearities of the neurons Identify suitable application task in the field of geolocation and optimize network and learning rules accordingly
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the topic: “AI-based processing of CAD models for automated planning of computer-aided manufacturing.” The candidate has the opportunity to pursue a doctoral degree (Ph.D.). Remuneration is 100% TVL E13
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focus is developing and characterizing metallic high-performance materials for/through additive technologies using experiments and computer-aided methods. Furthermore, the chair is dedicated