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position is embedded in a vibrant research environment that includes several PhD students and postdoctoral researchers. The project is a close collaboration between the Computer Vision Group at Chalmers
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together with relevant experience. You will have a strong technical background in machine learning, especially RL and LLMs. An ability to work independently and as part of a collaborative research team is
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August 2025 Apply now Machine Learning models are increasingly important in the atmospheric sciences. After training, they can emulate model outcomes at a fraction of the computational cost of traditional
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on and defensive mechanisms for safe multi-agent systems, powered by LLM and VLM models. Candidates should possess a PhD (or be near completion) in Machine Learning or a highly related discispline. You
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on evaluating the abilities of large language models (LLMs) of replicating results from the arXiv.org repository across computational sciences and engineering. You should have a PhD/DPhil (or be near completion
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computational analyses of epigenomic/transcriptomic data and machine learning. Experience in single-cell omics data is desirable. The post holder will be responsible to develop pipelines for the analysis
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Machine Learning, Statistics, Computer Science or closely related discipline. They will demonstrate an ability to publish, including the ability to produce high-quality academic writing. They will have the
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properties of Li-rich three-dimensional materials for lithium battery cathodes using density functional theory (DFT), molecular dynamics, cluster expansion, machine learning computational techniques. This work
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scientific discipline—particularly in healthcare data science, medical informatics, or clinical machine learning—as well as demonstrated expertise in healthcare data analysis, machine and deep learning, and
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projects in computer vision research, with a particular emphasis on Spatial Intelligence, 3D Computer Vision, and 3D Generative AI. You should hold a relevant PhD/DPhil (or near completion*) in Computer