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external) . Position Overview : We are looking for a highly motivated and qualified postgraduate trainee to join the project team. This individual should have experience in python programming including
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with computational analysis of multi-omic data (e.g., structural variants, transcriptomics) using R or Python pipelines. Mentoring and Professional Development: The postdoctoral associate will work
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) be detail-oriented with programming experience in statistical software such as Stata, R, Matlab, or Python; (ii) have a strong quantitative background; (iii) be able to work independently to solve
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, Neuroimaging, Physics, or Biophysics, with strong quantitative and analytical skills and proficiency in MATLAB and/or Python. Experience with preclinical MRI/fMRI/MRS, rodent models, image processing
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background in epidemiological and statistical methods, including coursework and/or research experience in evidence synthesis. 3. Programming experience using large datasets (e.g., R, Python). 4. Outstanding
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single-cell/single-nucleus genomics and spatial transcriptomics Computational analysis skills in R and/or Python A record of first-author publication To apply: Please send a CV, a brief statement of
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experience in Python programming including experience with the Pytorch library and running deep learning models. We are looking for organized, enthusiastic applicants who work well in a team and can quickly
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(Python, Keras, Tensorflow, Pytorch, STATA). Additionally, she will receive training on the implementation of machine learning techniques for data analysis (deep learning, random forest modeling
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preparation and multi-omic data integration. Computational skills for data analysis (e.g., Python/R, workflow tools, and reproducible research practices). Prior work related to neurodevelopmental
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. Strong programming and data analysis skills in Python and PyTorch; solid software engineering habits (git, testing, reproducibility). Demonstrated research independence with one or more first-author