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Field
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data and potentially mixed modalities (waveform, DICOM images etc.) Data manipulation and analysis capability, e.g. machine/deep learning in R/Python or other available tools with an interest in
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construct design, and single-cell genomics workflows (particularly 10X Genomics Flex). A key aspect of this role involves project management and coordination across multiple research groups. The associate
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Professor Arbel’s lab in the context of a grant focused on developing multi-modal causal deep learning models to predict future disability progression and treatment response in Multiple Sclerosis
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. ● Proficiency in Python, R, or similar programming languages. ● Demonstrated ability to integrate and analyze diverse data types, including but not limited to: ○ Neuroimaging (e.g., fMRI, PET, DTI
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. The ideal candidate will also be expected to have quantifiable experience with: A variety of different neuroimaging methodologies. Using multiple programming languages, including R, Python, MATLAB and
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programming, modelling, or simulation (e.g. Python, MATLAB, C++, or similar platforms). Familiarity with numerical or simulation tools such as but not limited to ANSYS Fluent , ASPEN, COMSOL, or OpenFOAM
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Biomedical Sciences, Microbiology, or related fields; experience with anaerobic bacterial culturing, mass spectrometry data analysis; experience with omics analyses and coding (e.g. python, R); experience with
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. This position is responsible for coordination of data and data analysis activities across multiple studies. Specific Duties & Responsibilities Develop, manage, and database of survey data from multi-site study
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also discover new possibilities. Our supportive workplace fosters a culture of creativity, welcoming fresh perspectives and innovation at all levels. We value teamwork. You’ll collaborate across multiple
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and with frequent interruptions. Understand and follow directions. Prioritize work and handle multiple tasks simultaneously. Qualifications: Degree in Biology, Medicine, Information/Library Science