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to discover pathway‑level disease mechanisms. Build reproducible pipelines in R/Python Integrate proteomic signatures with neuroimaging, cognitive and neuropathology phenotypes. Write manuscripts, contribute
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. Familiarity with statistical analysis software (e.g., STATA, R, SPSS) or computer programming (e.g. C++, Python, R) and experience working with health-related data will be advantageous. The ability to work
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Investigator AssociateProfessor Christoffer Clemmensen “Pharmacologically leveraging neurotrophic factor signaling for sustained weight loss” Principal Investigator Professor Juleen R. Zierath “Deciphering
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proficiency in R or Python. • Strong organizational and communication skills. • Proven ability to work independently as well as collaboratively in a team setting. • Must be a U.S. citizen or hold a U.S
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physiology Coding proficiency (e.g., Python, R) and familiarity with deep learning tools are strong assets A strong publication record, critical thinking, and collaborative mindset Application Instructions
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learning and advanced statistical modeling * Proficient programming skills in Python and/or R, experience with machine learning and omics analysis libraries (e.g., scikit-learn, TensorFlow/PyTorch
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on July 29, 2025:https://forms.office.com/r/695ZQxJt9G --- Applicants Must: Demonstrate: academic excellence and leadership in the research domain, high potential for success in their chosen fields, strong
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science, drug discovery, or related fields are encouraged to apply. Strong computational backgrounds, proficiency in at least one programming language (e.g., R, Python, Perl, C++, Java) and knowledge
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, techniques or methods and ability to contribute to developing new ones Demonstrate knowledge of bioinformatics resources such as annotation tools and databases Demonstrate proficiency in R/BioConductor and
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journals. Have experience in: (i) integrating single-cell and spatial multi-omics; (ii) computational programming in R, Python (and other common computer languages); (iii) competence/interest in analysing