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Field
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Your Job: Adaptive Control Theory (ACT) provides mathematically grounded and robust learning rules, prescribing that neurons should be diffusively forced toward a teacher trajectory and achieve
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-training that facilitate few-shot adaptations. The research will show how the complementarity of event-triggered learning and meta-learning can drastically increase RL efficiency at test time. The co-design
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help in shaping the change! We support you in your work with: TEAM & ENVIRONMENT: You will work in a motivated team with an international and interdisciplinary focus – at one of the largest research
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dynamics of these devices to perform complex learning tasks with extreme energy efficiency. Your Job: Develop and apply meta-optimization that can automatically search for the best algorithm-hardware pair
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the opportunity to contribute to collaborative efforts at the interface of data science, imaging, and materials research. You will strengthen the data science and machine learning activities of the IAS-9 with
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research experience academic publication record willingness to learn German For further questions please contact Dr. Marc Buckley ( marc.buckley at hereon.de ). We offer you an exciting and varied job in a
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learning, or signal processing; familiarity with microscopy data is an asset but not required Interest in foundational machine learning research with applied impact in scientific imaging Demonstrated
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Your Job: Develop AI pipelines that translate -omic signatures into dynamic model parameters Implement reinforcement-learning agents that optimise model performance Collaborate closely with
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academic publication record willingness to learn German For further questions please contact Dr. Marc Buckley (marc.buckley@hereon.de ). We offer you an exciting and varied job in a research centre with
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of Europe’s biggest research centers and help us to shape change! Are you eager to pursue a four-year doctoral project that bridges scientific disciplines? Are you excited by complex societal challenges