UC Davis is recruiting multiple postdoctoral scholars in translational data science to participate in DataLab’s 2-year TRANSCEND Postdoctoral Fellowship Program.
The intent of the TRANSCEND cohort program is to create a community of postdoctoral scholars in translational data science. Each of those fellows will be attached to a specific project(s) and mentors, and will participate in cohort training and leadership activities at the UC Davis DataLab. For this inaugural program, we are seeking motivated and enthusiastic postdoctoral fellows to conduct novel work and develop translational data science approaches for cardiology, radiology, public health, and epidemiology. Selected candidates will be joined by additional TRANSCEND postdocs working in information science, ocean health science, and potentially other domains for a cohort of at least 5 scholars.
All candidates must hold a PhD, MD, or MD/PhD in a field related to Science/Medicine or Data Science, i.e., either in Computer Science, Statistics, Machine Learning, Information Science, Health Informatics, etc., OR in an applied domain with a research background that contains a significant emphasis on quantitative approaches and skill sets, data analysis and high-level programming, and expertise in applying those skills in the biomedical or other scientific domain.
Scholarly independence, the ability to manage scientific projects, and excellent written and oral communication are essential. Candidates must have the desire to work in collaborative cross-disciplinary research projects. Ability to be on-site 25+% of the time and to attend in person bi-weekly cohort meetings is expected.
Projects and additional qualifications
- Cardiology: Develop AI/data science algorithms for cardiovascular medicine to discover the molecular determinants of atrial fibrillation. The work will involve developing methods for integrating multiple clinical and test data from clinical studies. The postdoctoral scholar will work under the direction of UC Davis Health MDs Chiamvimonvat and Srivatsa, and a mentor from the DataLab faculty fellows/affiliates in Engineering/ Computer Science/Statistics, on all aspects of the research including algorithmic design, training, and evaluation, data preparation, and evaluation. The postdoctoral scholar will also assist with scientific communication including conference presentation, journal manuscript preparation and submission, and data/code management preparation and publication.
- Radiology: Deep learning algorithms for the interpretation of digital subtraction angiography. The postdoctoral scholar will work under the direction of MD Goldman and a mentor from the DataLab faculty fellows/affiliates in Engineering/Computer Science/Statistics, on all aspects of the research including algorithmic design, training, and evaluation, data preparation, and evaluation. The scholar will assist with computing infrastructure. The postdoctoral scholar will also assist with scientific communication including conference presentation, journal manuscript preparation and submission, and data and code management preparation and publication. Proficiency with Python and machine learning/AI frameworks such as PyTorch or Tensorflow and experience with software development on and administration of a Linux open-source stack is expected. The following experiences are a plus: bioinformatics and medical imaging; Source control management software and open source development life cycle; Having worked in an environment subject to regulatory compliance requirements.
- Biomedical Informatics: Developing and evaluating methods for clinical and public health informatics systems, knowledge modeling, digital phenotyping, and workflow engineering. In particular, the scholar will be developing new tools and methods for designing, discovering and characterizing clinical phenotypes within patient electronic medical record data and real world data for predictive health outcomes. Approaches will include the systems and workflows involved in using identified and deidentified patient data at scale, and the application of machine learning and natural language processing. The postdoctoral scholar will work under the direction of Dr Anderson and a mentor from the DataLab faculty fellows/affiliates in Engineering/Computer Science/Statistics, on all aspects of the research including algorithmic design, training, evaluation, and data preparation. The scholar will assist with computing infrastructure. The postdoctoral scholar will also assist with scientific communication including conference presentation, journal manuscript preparation and submission, and data and code management preparation and publication.
- Epidemiology: Applying AI and other methods to provide near-real-time updates and optimization of risk rankings for viruses with the greatest risk to spillover to humans. The postdoc will integrate these results and workflow into the SpillOver webtool developed by the UC Davis Institute for Pandemic Intelligence (IPI), which aims to help the community identify viruses of pandemic potential and inform vaccine target selection. The postdoc will conduct this work under the general direction of the UC Davis Grand Challenges Vice Provost, Dr. Jonna Mazet, where they will support this and other strategically important projects involving computational methods by designing analytical models and implementing them in operational and research environments. Development of peer-reviewed publications and conference presentations on updated risk rankings and high-risk viruses, based on the expanded information collected through artificial intelligence, and recommendations on updated international standards for viral risk rankings will be key. More information about this specific postdoc position including additional qualifications and application details can be found at https://recruit.ucdavis.edu/JPF05464. Applications for this position can be submitted directly as listed on the recruit website, or as specified in this cohort call by emailing materials to firstname.lastname@example.org.
Mentorship: Each postdoc fellow will work with 2-3 mentors, at least one from a science or medical domain and at least one from DataLab’s faculty fellows/affiliates in engineering/math/statistics or a related data science domain. The postdocs will generate individualized development plans with their mentors, and are expected to meet regularly with them. Additional mentorship will be available through DataLab’s research services. The postdoc cohort will be facilitated by DataLab.
Training: In addition to mentorship and individualized training administered by their mentors, postdoc fellows will be expected to engage in DataLab’s Affiliates program which includes professional development, leadership, and instructor training. Postdoc fellows will grow expertise by applying these skills to ongoing and new activities including participating in workshops, seminars, Research and Learning Clusters, consultations, etc., at DataLab.
Community Building and Outreach: The postdoc fellows will be expected to participate in data science community initiatives, e.g., regularly present work, organize interest groups, etc.
Events: Fellows will be invited to several leadership and professional growth events throughout the year, specifically developed for the cohort.
Expectations of Postdoctoral Fellows:
- Be collaborative, with active interest in translational data science
- Work with at least 2 mentors (e.g., one science/medical and the other in STEM) and have specific goals for their time as postdocs
- 60% time spent on collaborative projects and initiatives directed by mentors
- 40% time spent on directed professional development, typically comprising:
- 20% of time spent on training efforts and cohort activities
- 20% of time spent in leadership roles in a data science community initiative
HOW TO APPLY
Please submit the following items as one pdf document titled “Your-Last-Name_transcend-application”:
- Curriculum Vitae, including listing of pertinent coursework, published papers, awards, etc
- Cover Letter
- Statement of Research in which you describe your interest in and relevant experience for one or more of the specific projects above
- Statement of Contributions to Diversity, Equity, and Inclusion – Contributions to diversity, equity, and inclusion documented in the application file will be used to evaluate applicants. Visit https://academicaffairs.ucdavis.edu/faculty-equity-and-inclusion for guidelines about writing a statement and why one is requested.
- Transcripts from your graduate institution and undergraduate institution, if applicable (optional but strongly encouraged).
- References: Names and emails of 3 recommendation letter writers
Send the application pdf document to email@example.com with the subject line “TRANSCEND Postdoc Application, Position X,” where X is the project name: Cardiology, Radiology, Biomedical Informatics, Epidemiology. Send reference letters directly to firstname.lastname@example.org.
Applicants who want to be considered for more than one of the projects must name each project in the email subject line (for routing) and describe in their cover letter their interests and qualifications pertaining to each project. Initial review will begin July 23, 2023. Start dates are expected between September 2023 and January 2024. The positions are open until filled. Questions can be directed to email@example.com.