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will disrupt today’s most vibrant research frontiers: Embed model-based AI into self-supervised pre-training pipelines Finetune multimodal deep learning models that answer diagnostic questions about X
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cooperative perception setting. Semantic-Aware Compression & Network Information Theory: Derive new rate–distortion–reliability bounds, design adaptive codecs that prioritise safety-critical bits, and close
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-mentioned methods Provide guidance to PhD students Disseminate results through scientific publications Prepare research proposals to attract industry partnerships as well as national and European grant
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partnerships and attract national and European grant funding Mentor and being involved in the supervision of PhD students on an everyday basis, offering guidance and support in their research, while co-authoring
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the equipment. The experimental work will be carried out in close collaboration with a Ph.D. candidate whom you will be co-supervising and another post-doc focusing on new LCE chemistry adapted to the procedures
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FWO-UGent funded bioinformatics postdocs: Unveiling the significance of gene loss in plant evolution
adaptation, speciation, and biological innovations. This project aims to redefine our understanding of gene loss alongside gene gain in plant evolution, focusing on developing novel genomic approaches
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international conferences and workshops Implementing proof-of-concept solutions Providing guidance to PhD, MSc, and BSc students Organizing relevant workshops and demonstrations Contributing to the acquisition
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. Profile You hold a PhD in biomedical sciences, biotechnologies or related disciplines. You have spent at least 12 months of the three years prior to the start date as a postdoctoral scholarship holder
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researcher interested in studying human-associated microbial communities in health and disease. The ideal candidate has the following qualifications: A PhD degree in bioinformatics, computational biology
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postdoctoral researcher interested in studying human-associated microbial communities in health and disease. The ideal candidate has the following qualifications: A PhD degree in bioinformatics, computational