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. You will also collaborate on the analysis and evaluation of collected data and ensure that all data are properly anonymised before publication. Where to apply Website https://www.academictransfer.com/en
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and experience with modern deep learning frameworks (e.g. PyTorch) Solid background in machine learning, ideally with experience in NLP, large language models, or sequence modeling Interest in clinical
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experience of generative AI users. The ideal applicant will have an established or emerging research agenda focusing on AI with expertise relevant to natural language processing (NLP), generative AI, applied
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Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL), particularly in Natural Language Processing (NLP) and Computer Vision (CV) Familiarity with genomic and bioinformatic databases
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for Agricultural Education o Focus on NLP, machine learning, and learning analytics as they relate to communication and education. This includes AI-supported curriculum design and evaluation in agricultural
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. Co-designing and programming innovative experiments using web data; 3. Working with or assisting in the development of automated classification systems (NLP, Large Language Models); 4. Analysing and
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experience will suffice for research engineers. Applicants with skills in Video Analytics, NLP (Natural Language Processing) or any of the following would be preferred: Caffe, Spark ML, Keras, PyTorch
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(NLP) algorithms applied to electronic health records (EHR) to understand cannabis-related harms in aging PWH and people without HIV. The position will entail collaborations with several investigators
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establishment in 2014, the CAMeL Lab has produced over 200 publications and 20 language resources and tools. The lab website is http://www.camel-lab.com/ . Google Scholar of the lab is at http://scholar.camel
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establishment in 2014, the CAMeL Lab has produced over 200 publications and 20 language resources and tools. The lab website is http://www.camel-lab.com/ . Google Scholar of the lab is at http://scholar.camel