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, retrieval products) Strong programming skills in Python Experience in machine learning, ideally including deep learning architectures such as graph neural networks, transformers, or spatio-temporal models
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skills Ability to work with nuclear industry data Good understanding of the nuclear sector in Canada Proficiency in at least one programming or statistical software package (Python, MATLAB, R, or Stata
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doctoral degree in epidemiology, biostatistics, bioinformatics, microbiology, or a related field Strong quantitative and statistical skills, with proficiency in R or Python Experience working with
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analytic workflows on an active NIH-funded research grant. Applicants should have a bachelor’s degree in an analytic field (data science, AI, or bioinformatics) and demonstrate familiarity with R and Python
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of computational neuroscience concepts - Expertise in dynamical systems theory - Knowledge of machine learning - Experience with neural data analysis ### Technical Skills - Advanced scientific programming (Python
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datasets • Contribute to data processing and analysis (R/Python; training provided as needed) Research Operations • Maintain study documentation and regulatory materials • Participate in lab meetings and
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state of the art AI and analytic tools (e.g., Go, Python, Rust, Spark, PyTorch, TensorFlow) to create consistent and reliable software. You will utilize tools and methods such as continuous integration
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with biological datasets; experience with R, Python, or omics analysis pipelines is advantageous but a keen willingness to learn is equally valued Language Requirements: Applicants must demonstrate
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- Knowledge in programming in Python or R - Familiarity with machine learning or deep learning methods is a plus - Interest in plant genomics, evolutionary biology, or comparative genomics - Proficient in
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, BWA, STAR, GATK, VarScan, DESeq) Proficiency in Linux and programming languages such as Python, R, MATLAB, or Perl Excellent written and verbal communication skills in English, along with a