The Department of Radiology, University of Wisconsin - Madison, School of Medicine & Public Health is seeking a Scientist who will play a key role in developing and translating next generation radiomics (machine learning in radiology imaging) methods for projects ongoing in Dr. Pallavi Tiwari's lab. The research conducted by Tiwari lab utilizes medical imaging and clinical data to build and optimize AI and machine learning models that identify computerized image-based phenotypes, and their associations with genomics and histopathology for disease characterization, with the aim of developing personalized diagnostic tools towards improved early diagnosis, prognosis, and response to treatment for neurological conditions and other diseases. More information about our research and publications can be found at https://idia.labs.wisc.edu/. The Scientist will work on interdisciplinary and translational research in personalized diagnostics towards early diagnosis, prognosis, and response to treatment for brain tumors, neurological disorders, and other diseases (e.g., breast cancer, pancreatic cancer, liver disease). The Scientist will be responsible for identifying clinically translatable research problems relating to these diseases; developing research methodologies and experiments to identify and utilize radiomic, radio-genomic, and radio-pathomic phenotypes to better characterize these diseases (e.g., building a classifier to predict disease progression or the risk of developing advanced cancer); and training students. ADDITIONAL JOB DETAILS: This position may require some work to be performed in-person, onsite, at a designated campus work location. Some work may be performed remotely, at an offsite, non-campus work location. Multiple Titles: Scientist I, Scientist II, or Scientist III. Applicants for this position will be considered for the titles listed in this posting. The title is determined by the experience and qualifications of the finalist. Candidates who demonstrate the following knowledge, skills, and abilities will be given first consideration; Candidates should have demonstrated ability to work effectively in a collaborative manner with faculty and staff, as well as other institutional representatives; Strong organizational, written, and verbal communication skills; High levels of critical thinking, excellent technical skills, and a strong track-record of accomplishment and productivity in research as evidenced by high-quality publications related to medical imaging, oncology, and/or machine learning and artificial intelligence.
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Job Type
Full-time
Career Level
Mid Level
Education Level
Ph.D. or professional degree
Number of Employees
5,001-10,000 employees