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to algorithms with actionable performance guarantees. More specifically, the research will revolve around the following theme: High probability convergence in stochastic optimization under heavy-tailed noise
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-loss events undermine statistical confidence. The aim is to develop i) edge intelligence (on-turbine smart algorithms for data preprocessing), ii) resilient data movement (error-tolerant, cybersecure
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Postdoctoral position in the development of an AI-based phenotyping system for high-throughput sc...
quantitative and statistical modelling approaches to biological systems (including crop genetics, host-pathogen interactions, pathogen population genetics, evolutionary biology...). The candidate will work in
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quantitative and statistical modelling approaches to biological systems (including crop genetics, host-pathogen interactions, pathogen population genetics, evolutionary biology...). The candidate will work in
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, and protein structure prediction by artificial intelligence algorithms. The goal is to generate functional models of multimeric protein complexes and how they assemble as a guide to understand disease
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. Experience with phase retrieval algorithms, clean room use and e-beam lithography are beneficial. The candidate will be expected to participate at international user facilities and thus will be expected
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visions of AI-native data systems capable of querying unstructured data declaratively, you will design and evaluate novel algorithms for extracting entities and relationships, while capturing provenance and
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candidate will develop and test novel user interfaces that integrate state-of-the-art Large Language Models (LLMs) with novel logic-based multi-robot planning algorithms. This work will be evaluated through
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algorithms aimed at predicting pathogen potential based on whole or partial genomes. You will also be responsible for integrating such tools into online accessible pipelines thus, providing the possibility
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systems, including integration of cyber-security. Enhance indoor climate by defining control strategies and developing control algorithms for demand-control ventilation, heating and cooling systems