University of California Irvine

The computational medicine lab led by Dr. Pratik Shah at UCI invites applications for a Postdoctoral Scholar position from outstanding Ph.D, MD or foreign equivalent applicants with strong academic computer science, biomedical informatics or statistics backgrounds.

The lab is interested in developing novel AI-based technology for quantification and real-world validation of clinical decision making. Recent research studies from the lab were published in Cell Reports Methods, Nature Digital Medicine, Cell press, IEEE machine learning conferences, Journal of American Medical Association, and Proceedings of National Academies of Science Engineering and Medicine workshops. Visit our websites for more information about the lab: https://faculty.sites.uci.edu/pratikshahlab/ ; https://www.pratiks.info/publications/all/

Applicants experienced in in solving critical challenges for developing biologically informed statistical methods and uncertainty estimations for training deployable AI models that establish causal relationships in clinical data will be given preference. The scholar will be responsible for training deep generative reinforcement AI models for learning predictive and prescriptive clinical decision-making from time-varying electronic medical records. You will formulate novel statistical methods for uncertainty quantification of patients’ outcomes and use unsupervised learning to discover biologically relevant disease subtypes. Determine feature importance for validating predictions and estimations from fully trained deep neural network models for correlative and matrixed molecular sequencing data. Opportunities to publish in leading journals and machine learning conferences, networking with government funding agencies, industry partners, foundations, and leading academic experts. Training in fellowship writing, teaching/mentoring, oral presentations and review of manuscripts will be provided.

Substantive inquiries about the position should be directed to:

Pratik Shah PhD

Assistant Professor of Pathology and Laboratory Medicine

UC Irvine, School of Medicine

pratik.shah@uci.edu

Interested candidates should complete the application profile and provide a CV, cover letter including career motivation and why you are interested in joining the lab and an Inclusive Excellence Activities Statement. Guidance for Writing Inclusive Excellence Activities Statement – Academic Personnel (uci.edu)

Initial appointments are for two years & renewal is based on performance and available support.

Application Procedure - TO APPLY: Please log onto UC Irvine’s RECRUIT located at: https://recruit.ap.uci.edu/JPF08838

Department: https://www.pathology.uci.edu/

QUALIFICATIONS

Basic qualifications

• Appointment as a Postdoctoral Scholar requires a doctoral degree (e.g., Ph.D., MD) or the foreign equivalent in computer science, biomedical informatics or statistics

Preferred qualifications (required at time of application)

• Experience in applied statistics i.e., probabilistic models and Bayesian models for uncertainty quantification, causality estimates for explainable deep learning, reinforcement learning.
• Experience in open-source deep learning frameworks such as TensorFlow or PyTorch
• Experience using Python, C++, and Java, Linux
• Experience in writing software in a team-oriented environment with version control, issue tracking, and code review with Python (Scikit-Learn Numpy, and Pandas, MATLAB and C++)
• Familiarity with data processing techniques for text and time series clinical data, and knowledge of MySql, MongoDb, databases.
• Track record of writing and publishing research papers in peer-reviewed journals or top machine learning conferences
• Strong analytical and organizational skills; detail-oriented
• Committed to mentoring others.

A reasonable estimate for this position is $64,480-$77,327. See Postdoctoral Scholar – Fiscal Year Rates “Off-scale salaries” and other components of pay, i.e., a salary that is higher than the published system-wide salary at the designated rank and step, are offered when necessary to meet competitive conditions.