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Post-doctoral Position in AI Causal models for Synchrotron Anomaly Detection H/F This post-doctoral position is part of a collaboration between LIAD (Laboratory of Artificial Intelligence and Data
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and educational issues with the common goal of contributing to an inclusive, open and resourceful society. Your role The Postdoctoral researcher will be working in the Institute for Lifelong Learning
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of the project is to exploit such data to develop generative models for aptamer design. The candidate is expected to have a strong background in machine learning and statistical physics, with a real interest for
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interdisciplinary, and together we contribute to science and society. Your role We seek a highly motivated bioinformatician or computational biologist who is well versed in the statistical and machine learning
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Postdoctoral position: Developing a human lymphoid organ-on-chip to evaluate candidate mRNA vaccines
its throughput, with the objective of building a novel pipeline suitable for the preclinical evaluation of candidate vaccines. The project will be carried out in close collaboration with the team
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computational framework, integrated with deep reinforcement learning (DRL) methodologies for both gene-level and edge-level perturbation control, represents a significant advancement in the computational toolkit
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collaborate with other postdoctoral fellows under the supervision of Prof. Paul Avan, working with diverse datasets collected to improve the diagnosis and follow-up of hearing-impaired patients
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. It focuses on building AI skills, promoting trustworthy AI, and accelerating innovation through targeted training, micro-credentials, public engagement, and industry collaboration. Within
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-quality training and learning materials, and a sustainable plan. FSTM's main tasks are to contribute to the definition of the body of knowledge and competencies, assist in developing the skill tree used as
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found on hpc.uni.lu . The activities include classical HPC applications such as simulation and modeling, but also artificial intelligence and machine learning, bridging computational science, with data