We welcome engaged individuals to join our various research pursuits in the lab! We welcome trainees at all levels. Here are some current training and mentorship opportunities that the Baxter Lab is participating in. We especially welcome those from historically underrepresented backgrounds (see Dr. Baxter’s involvement with the UCSD Shiley Eye Institute Diversity, Equality, and Inclusion Committee here). If interested, please contact Dr. Baxter at email@example.com.
- UCSD Faculty Mentoring Program:
Program for mentored research for UCSD undergraduates.
- UCSD School of Medicine Independent Study Program:
Program for mentored research for UCSD medical students.
- UCSD MSTAR Program:
Funded summer research program for medical students between the first and second year of training. Open to all U.S. medical students.
- UCSD National Library of Medicine training program in Biomedical Informatics:
Programs for pre-doctoral and post-doctoral trainees in biomedical informatics. Dr. Baxter is an alum of this program and welcomes any NLM trainees for rotations in her lab!
- Shiley Eye Institute T32 Vision Research Training Program:
Dr. Baxter participates in the T32 training program to fund postdoctoral fellows in vision research and can co-mentor fellows working with the UCSD Computational Ophthalmology Group.
Postdoctoral fellowship in Artificial Intelligence / Retinal image analysis and personalized medicine at the University of California, San Diego, Shiley Eye Institute.
The fellowships require a doctoral degree and are normally awarded for two years. One fellowship is funded by a NEI Training Grant that requires that fellows be US citizens or permanent residents.
Retinal image analysis/computational ophthalmology/ personalized medicine:
Independent researcher to utilize deep learning for evaluating retinal images from spectral domain optical coherence tomograph (OCT), OCT angiography and other imaging modalities for clinical decision support, screening, telemedicine and personalized medicine applications. The ideal candidate will have demonstrated research expertise and strong interests in at least one of the following areas for 2-D/3-D medical image analysis: 1) statistical / mathematical / numerical analysis, 2) image processing / computer vision techniques, 3) deep learning for feature detection and/or automated diagnosis 4) high performance computing techniques for image analysis, and 5) telemedicine, digital health or related areas.
Candidates will have the opportunity to work on large longitudinal cohorts of patients with and without retinal diseases including the Diagnostic Innovations in Glaucoma Study (DIGS) and the African Descent and Glaucoma Evaluation Study (ADAGES). Postdoctoral research projects and training can be completed under the multi-disciplinary initiative, “Computational Ophthalmology”, among the Departments of Ophthalmology, Biostatistics, Computer Science & Engineering, Bioengineering, Neurosciences and the new Halicioglu Data Science Institute at UCSD with several opportunities to strengthen cross-discipline skills.
Candidates will have access to several computational / cluster resources including resources available through the San Diego Super Computer Center, AWS and the Altman Clinical & Translational Research Institute. Highly motivated candidates will also receive training and guidance in writing research grants and work with a multidisciplinary team of UCSD computer scientists, data scientists, vision scientists, clinical researchers and basic scientists.
Interested candidates should submit 1) a curriculum vitae, 2) a brief statement of research interests and 3) contact information for 3 references to:
Linda M. Zangwill, Ph.D. @ firstname.lastname@example.org
PhD or an equivalent degree in electrical engineering, computer science, image and signal processing, biomedical engineering, biomedical informatics, data science, mathematics, statistics or related discipline. Strong computer programming skills ( Python, C/C++/Java, MPI/clustermcomputing, MATLAB, or R) preferred. Excellent writing skills and history of productivity desirable.
Applications from individuals with disabilities or other underrepresented groups are particularly encouraged. Applications will be accepted until filled.