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of Mathematics and Natural Sciences at Heinrich Heine University Düsseldorf is inviting applications for the position of a Professorship for Machine Learning (open rank: W2 or W1 with tenure track to W2
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well as familiarity with machine learning workflows, natural language processing (NLP), and text-as-data methods. We are especially interested in applicants who demonstrate a strong substantive interest in using
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The Centre for Machine Learning within the Data Science and Statistics Section of the Department of Mathematics and Computer Science (IMADA) at the University of Southern Denmark invites
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that support the unit for area protection and marine spatial planning, as well as operations at SLU Aqua. Your profile You have documented expertise in marine ecology and computer vision and machine learning
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programming targeting analyses of large-scale assessment and/or survey data ●Advanced proficiency in Python for data analysis, machine learning, and NLP tools ●Experience with relevant statistical programming
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Position as Computational Analyst / Bioinformatician in RNA Therapeutics and Cardiometabolic Disease
seq like PSCSR-seq. Training PhD students and post-docs to analyze large-scale datasets and interpreting results. Provide input to projects in our group and help with illustrating complex biological
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on real-world health data analysis — including study design, data wrangling, phenotype development, data integration, and statistical and machine-learning methods — to accelerate project delivery
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at Sahlgrenska Academy of relevance include genomics, metagenomics, culturomics, proteomics, transcriptomics, software development, machine learning, and other statistical analyses of large-scale health data
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Data Science Investigator project (“LM2-SEC: Linguistically Motivated Language Model Security”). Your work tasks As a PhD student, you will conduct research at the intersection of Security, Safety, and
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The University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 1 month ago
engineering will be considered, particular emphasis is on computer systems and design aspects that enable real-world AI applications, including hardware-software co-design for machine learning, learning-enabled