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focused on Artificial Intelligence (AI)-driven retrosynthesis and reaction prediction. The successful candidate will develop advanced machine learning (ML) models to automate and optimize retrosynthetic
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of engagement. Read more at: Department of Computing Science Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data-driven
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network inference and modeling, machine learning and deep learning. Experience in working with Arabidopsis and plant genome data is a strong plus. The position is expected to continue for multiple years
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of machine learning techniques, programming and coding for data analysis, biomarker discovery, and collaboration with clinicians and students. Additionally, the candidate will be responsible for grant writing
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will engage in research that includes applied machine learning, systems building, and Internet measurements. Key Responsibilities: Contribute to driving and developing the lab's research directions and
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ANR project which involves a puri-disciplinary team of researchers including machine learning, speech science, cognition and behavioural studies. This Post Doctoral position will be co-supervised by
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Molecular Biology seeks a Postdoctoral Associate to join the research group of Professor Fenghua Hu. Details of Dr. Hu’s laboratory, ongoing research projects, and recent publications can be found at https
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. Unsupervised machine learning approaches will be used to identifiy key dimensions of circadian rhythm associated with dementia subtypes. This requires a very good level in statistics and R programing as
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, ideally molecular dynamics and/or DFT. Scientific programming skills, particularly in Python, are expected. Familiarity with machine learning or generative AI methods applied to materials would be a strong
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. For more information, visit us on line at: http://www.unlv.edu EEO/AA STATEMENT The University of Nevada - Las Vegas (UNLV) is committed to providing a place of work and learning free of discrimination