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(LLM), and optimization algorithms. Collaborating with our team to transform research insights into practical, impactful solutions. Staying abreast of the latest advancements in ML, transformers, graph
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data for urban characterization. The work includes developing algorithms, performing large-scale analyses, and collaborating with partners across disciplines in remote sensing, urban studies, and climate
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AI methods and genetic algorithms Prior publication experience at top robotics and AI conferences (ICRA/IROS*/RSS/NIPS/CoRL) / journals (RAL/TRO/IJRR/RAM) is necessary *If you are attending IROS 2025
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properties. In this project, we will apply machine learning and optimization algorithms in order to achieve the design of such nanophotonic structures. As a postdoc you will be part of the Condensed Matter and
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apply machine learning and optimization algorithms in order to achieve the design of such nanophotonic structures. As a postdoc you will be part of the Condensed Matter and Materials Theory division, a
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algorithms to enhance the design optimization process Create predictive models using Python-based frameworks (e.g. scikit-learn, PyMC) to accelerate design iterations Integrate ML approaches with finite
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both academic research and industrial applications. In addition to theoretical research, the work might involve implementing new algorithms in the SCT tool Supremica, which is developed by the Automation
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and ability to work in an interdisciplinary and international environment Proficiency in written and spoken English. Meritorious Experience with multiple crystal growth techniques and/or diverse
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interdisciplinary and international environment Proficiency in written and spoken English. Meritorious Experience with multiple crystal growth techniques and/or diverse materials classes Familiarity with transport
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for a two year postdoctoral position to characterize the statistics of brain activity and relate it to the underlying network properties. Recent data has revealed the multiple ways brain activity