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programming of algorithms. The use of programming languages such as Python, R, SQL, and C++ will be a daily part of the project, and proficiency in these languages is required. However, additional datasets will
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Python is required. Programming in C or C++ is a plus. Background in statistical genomics, longitudinal modeling, non-parametric statistics, machine learning and deep learning are preferred and encouraged
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prostate tumor samples. This position requires a strong background in both experimental proteomics and computational data science (R and Python), with an emphasis on LC-MS/MS workflows and long-term cohort
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potential vulnerabilities is a strong plus Proficiency in a major programming language (e.g., Python, Java, or C++) Familiarity with cybersecurity tools and methodologies, including vulnerability assessment
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, particularly in C++ and Python Good communication skills in spoken and written EnglishInterest or prior experience in machine learning techniques is considered an asset. You may expect a multifaceted and
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, physics, mathematics, computer science, or related fields Demonstrated hands-on experience with machine learning techniques Strong programming skills (Python preferred) Experience analyzing time-series data
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' datasets - genomics transcriptomics, and proteomics Proficiency in R, Python, and other programming languages Expertise in Linux, Git, Docker, and other high-performance computing environments Excellent
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) Familiarity with using R and/or Python for answering biological questions (desired) WE OFFER: An international, multidisciplinary, and creative working environment Innovative technologies Excellent
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experience in machine learning methods, tools, and platforms. Proficiency in Python, with demonstrated software development experience. Hands-on experience in MLOps, including the design and deployment
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Nature Careers | Vancouver South Shaughnessy NW Oakridge NE Kerrisdale SE Arbutus Ridge, British Columbia | Canada | 15 days ago
interdisciplinary collaboration. Demonstrated programming skills, preferably in Python (e.g., PyTorch, NumPy, pandas, polars). Experience with spatial and/or temporal data analysis (geographic data, satellite imagery