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departments, IRISA is a center of excellence whose scientific priorities include bioinformatics, system security, new software architectures, virtual reality, big data analysis, and artificial intelligence
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, enhanced sampling, QM/MM) Experience improving performance and scalability of simulation workflows via: Parallelization and performance engineering GPU/accelerator optimization Algorithmic innovation
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IFREMER - Institut Français de Recherche pour l'Exploitation de la MER | Brest, Bretagne | France | 15 days ago
processes structuring these systems. Among the topics covered, the unit places a strong emphasis on trophic ecology, focusing on benthic–pelagic coupling and the structure of coastal food webs. Research in
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challenging and impactful research and development programs in healthcare informatics, bioinformatics, high performance computing and deep learning. We have a collaborative environment focusing on designing
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ecomorphological outcomes significantly parallel. As a next step, it is vital to dig more deeply into the molecular mechanisms driving these patterns. This project will examine replicate divergences into specialist
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large research team. Job Description Primary Duties & Responsibilities: Designs, develops, and implements: Algorithms and computer software for omics-based data sets [high-throughput, massively parallel
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initiatives aimed at scaling laboratory throughput capacity. Reporting to the User Support Analysis Group Lead, this position leverages bioinformatics tools to process data from multiple sequencing platforms
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Classification Title: Research Software Engineer II Classification Minimum Requirements: RSE Level I: A Bachelor’s Degree in computer or physical science, statistics, bioinformatics, analytics
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). Excellent interpersonal skills and ability to work with diverse group of staff. Excellent organizational and computer skills and record-keeping habits. Experience juggling multiple parallel efforts and
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Description Primary Duties & Responsibilities: Implements: Algorithms and computer software for analyzing omics-based data sets [high-throughput, massively parallel genomic/proteomic/clinical]; Data management