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Koziarski Lab - The Hospital for Sick Children | Central Toronto Roselawn, Ontario | Canada | about 2 months ago
, reinforcement learning, diffusion, and flow matching, guided by practical considerations of high-throughput chemical synthesis. In addition to algorithm development, the candidate will have the opportunity
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and conferences. Proven experience in design and implementation of deep learning algorithms. Outstanding programming skills in Python. Extensive experience working on one or more of the following areas
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experience in root phenotyping systems and experiments is desired. Experience: The ideal candidate has a good knowledge of plant root systems, methods for phenotyping root systems, and plant genetic analyses
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The University of British Columbia (UBC) | Vancouver UBC, British Columbia | Canada | about 2 months ago
optimization and coordination algorithms for BC Hydro–cVPP interaction and evaluate grid performance through simulated case studies, and analyze service offerings and pricing via case studies and apply social
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initiative that will advance our understanding of how genetic factors influence cardiac structure and function, and yield AI models that link phenotypic findings with genetic data to predict CVD risk and
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Institut national de la recherche scientifique (INRS) | Varennes, Quebec | Canada | about 3 hours ago
. Responsibilities include (but not limited to): Lead the development of the NC-ARPES technique (hardware, post-processing algorithm, theory, data interpretation) Propose and perform new TR-ARPES studies of quantum
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: Computer Architecture Algorithms and Optimization Health Research Human-Computer Interaction Machine Learning and ML Foundations Machine Perception Natural Language Processing (including Information
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, biology, genetics laboratory experience is an asset Experience collaborating as part of a multi-disciplinary and international research team, and attention to detail for methodological documentation
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, and interpreting models, Analyzing genetics data (e.g. GWAS, eQTLs), including predicting variant effects, stratifying patients, identifying desired patients for recall, Designing, synthesizing, and
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analysis pipelines (e.g., Seurat, Scanpy, ArchR). Prior exposure to high-throughput screening or pooled genetic perturbation methods. What we offer A supportive and collaborative research environment within