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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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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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' 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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Nature Careers | Vancouver South Shaughnessy NW Oakridge NE Kerrisdale SE Arbutus Ridge, British Columbia | Canada | 2 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
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mathematics, computer science, physics, biomedical or electrical engineering or similar disciplines. Good programming expertise (Matlab, C++, Python or equivalent) and experience with the Linux operating system
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essential. Experience with MATLAB or Python computer programming for neuroimaging data analysis is essential. Experience in MRI and/or EEG acquisition and analysis is desirable. Experience working on research
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;Knowledge of bioinformatics tools relevant to gene editing and transcriptomics (e.g., Benchling, SnapGene, Geneious, R, Python);Proven track record in publication and in scientific outreach. Personal Skills
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development. Experience with implementing statistical learning or machine learning (e.g. Bayesian inference, deep-learning). Programming skills in Python and experience with frameworks like PyTorch, Keras, Pyro
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/ NiFi/ Knime, Programming in Python and SQL. Experience with version control systems (Git, CI/CD); Java/Scala is a plus. Familiarity with containerisation and orchestration like Docker and Kubernetes