"HMS - Associate in Biomedical Informatics (Zitnik Lab)"

Position Description

The Associate will engage in academic research and training activities focused on biomedical research methods in healthcare. Under the close supervision and mentorship of Dr. Zitnik, the Associate will: 1) Explore and learn about state-of-the-art techniques for constructing, maintaining, and contextualizing biomedical datasets by reviewing recent academic literature and attending lab seminars, 2) Develop prototype implementations of systems, receiving feedback and guidance from Dr. Zitnik, 3) Participate in the evaluation and benchmarking of these prototypes through hands-on, mentored research projects, 4) Assist with data science analyses related to medical decision making in global health, acquiring new skills and methodologies through supervised practice, 5) Contribute to the preparation of research reports and scientific manuscripts, with structured mentoring in scientific writing and publication, 6) Support the dissemination of research by developing tutorials, user documentation, and example code, and by sharing educational materials with the broader research community, 7) Attend and present at lab meetings, reading groups, and educational workshops to further develop research and communication skills.

Basic Qualifications

Bachelor's degree in computer science or closely related field.

Additional Qualifications

Demonstrated interest in academic research, scientific inquiry, and the pursuit of new knowledge in data science, or biomedical informatics. Strong programming skills and familiarity with deep learning platforms. Experience, coursework, or training in data processing techniques and methods for multimodal biomedical data or knowledge graphs.

Contact Information

Heather Viana
10 Shattuck St
Boston, MA 02115
Email: heather_viana@hms.harvard.edu

Salary Range

$65000

School: Harvard Medical School

We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, gender identity, sexual orientation, pregnancy and pregnancy-related conditions or any other characteristic protected by law.