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systems using computer vision, quantitative image analysis, deep learning methods for detection, diagnosis, and quantitative analysis of abnormalities with multimodal data, including clinical and
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effectively. Strong skills in stakeholder engagement, community-based participatory research or co-design methods. Proficiency with data analysis software (e.g., NVivo, SPSS/STATA/R). Familiarity with
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related field, have a strong record of research productivity (e.g., publications and software) in mass spectrometry-based proteomics, and possess substantial experience developing algorithms and pipelines
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and training. Professional Development: Develop and maintain a formal Individual Development Plan (IDP). Actively pursue independent research interests and apply for internal/external fellowship funding
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regulatory network. Be involved in manuscripts/reports preparation. Work closely with other team members and train new members Required Qualifications* PhD in Bioinformatics/Statistics Strong experience in
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* PhD in Molecular Biololgy or related fields. Skills and experience with basic molecular methods including but not limited to processing/preserving/analyzing mammalian organ tissue (mice), culture
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automation, computational drug design, machine learning, and software engineering. The ideal candidate will contribute to innovative research and the development of advanced computational tools within our lab
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presentations, and mentoring students of all levels. Participate in funding, deliverable preparation, and meetings. Document work, produce open source data, software, and results; publish strong technical papers
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methods, and the social and contextual factors that shape health and contribute to health inequities. The successful candidate will have the opportunity to develop a mentored research agenda while
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with animal husbandry Required Qualifications* PhD in engineering, physics, or a closely related discipline 4+ years research experience in areas such as the jamming and deformation of granular materials