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to the Terascale Project Knowledge of research methods relevant to AI for materials science Knowledge of one or more of the following areas: machine learning interatomic potentials, generative AI, automated and
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computational chemistry, reaction network analysis, and machine learning for organometallic catalytic reactions. 2. Design of membrane-permeable macrocyclic peptide drugs via machine learning structure
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: A good Bachelor’s degree or Master’s degree in Computer Science, Engineering, or a related discipline, with demonstrated experience in Artificial Intelligence (AI) / Machine Learning (ML) research
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. · Knowledge of molecular biology, cell biology, immunology, neuroscience, or ophthalmic research is considered an asset. · Experience with single-cell genomics, spatial transcriptomics, machine learning
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to the lab's ongoing research projects, while also develop their own scientific niche. An ideal candidate will bring new expertise and experience to the lab, while showing interest in learning new skills
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, or ophthalmic research is considered an asset. · Experience with single-cell genomics, spatial transcriptomics, machine learning, artificial intelligence, or translational biomedical research is considered
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of novel computational/biostatistical/machine learning methods for the integration of multiple, diverse dataset and the synthesis of hypotheses around the molecular mechanisms that drive the co-occurring
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(kidney biopsy, serum, urine) for comprehensive biomarker profiling. Utilization of machine learning and image processing for advanced tissue analysis. The Herman B Wells Center for Pediatric Research
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Department of Computing Postdoctoral Fellow (four posts) (Ref. 260915011) [Appointment period: each for eighteen months] Duties The appointees will assist the project leader in the research project
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to find out more about the Department. About you This is a post for a medical doctor and would be especially suitable for trainees in infectious or tropical diseases, medical microbiology/virology