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learning can improve software architecture recovery, how to optimize machine learning models at compile and runtime, and autonomous agents for software development. Part of the research is conducted through
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research questions. This postdoctoral scholarship offers the opportunity to be a part of this AI revolution by developing novel neural network architectures specifically optimized for plant genomic data. Our
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for tens of kilometers length. In this project, you as a postdoctoral researcher will mainly carry out: optimization of both fiber preform preparation and fiber drawing processes so as to reliably fabricate
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in electric vehicle applications. Scientifically, the following parts will be included in the research: a) Fabrication and optimization of large-scale hBN films of high quality with high in-plane
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driving the integration of methods in artificial intelligence (AI) and machine learning (ML) to improve and optimize workflows when developing therapeutic antibodies Duties – what we expect from you As an
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evaluation frameworks and/or the development of energy system optimization models. The research is applied and closely linked to industrial interests and needs. About the research Our research aims to provide
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automated planning, reinforcement learning, logic or combinatorial optimization. Furthermore, candidates should have excellent study results, very good programming skills and high proficiency in oral and
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computational biology with a focus on developing new and scalable computational models (e.g. deep learning, machine learning, optimization or statistics) or integrating data-driven applications to address
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to development projects. Establishing a research program in translational computational biology with a focus on developing new and scalable computational models (e.g. deep learning, machine learning, optimization
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to optimize antenna performance. For more information, https://ant.eecs.kth.se/SEE-6GIA/ (SEE-6GIA) Contact person: Mats Gustafsson Research direction 2 This project develops a distributed radar system