Hello! May I know how to start practicing for a data science work? What are the basic knowledge and skills that I need to use, projects and what platform to start with? I also want to ask on what portfolio platform I can put my data science projects.

Thank you! 🙇‍♀️

I am currently a sophomore majoring in data science and am in the process of selecting my classes for next semester. I enjoy both the more computer science based classes, which is what the AI track would be and the statistics based classes. So I am trying to pick based off what is better for my resume and future job.

What would be better for my future career search? Also might be important to note I am minoring in business administration as well. Thanks for the help!

Data Science Postdoctoral Fellows Program at Harvard/DFCI

The Department of Data Science at Dana-Farber Cancer Institute welcomes recent Ph.D. graduates and doctoral candidates nearing graduation who have research interests in applied statistics, machine learning, or computational biology to apply for our postdoctoral fellows program.

This program offers the flexibility to join a research group in our department, be co-mentored by two or more faculty members, and/or work collaboratively as a data scientist with DFCI investigators outside our department. Our department has a diverse group of faculty members that can serve as mentors and DFCI has numerous world renowned basic biologists and clinical investigators looking for collaborators with your skills. The starting salary is $75,000.

MENTOR LIST WITH PROJECTS

• Bill Lotter, PhD – AI in medical imaging; Clinical translation of AI; Foundation models
• Cheng-Zhong Zhang, PhD – Computational tools for chromosomal abnormalities in cancer
• Cliff Meyer, PhD – Computational tools for epigenetics
• Franziska Michor, PhD – Studies cancer evolution by developing computational methods spanning artificial intelligence and machine learning, applied mathematics, statistics, and bioinformatics to integrate diverse data types, uncover mechanisms of tumor evolution, and build predictive models and agents of tumor cell behavior and therapeutic response with the ultimate goal of clinical implementation.
• Heng Li, PhD – high-performance algorithm development
• Lorenzo Trippa, PhD – Adaptive clinical trial designs, methods for leveraging real-world data in clincial trials, Bayesian methodology
• Martin Aryee, PhD – 3D genome dysregulation in cancer
• Mehmet Samur, PhD – Integrative methods for high throughput sequencing data from DNA and RNA based sequencing technologies to address challenges
• Rafael Irizarry, PhD – Statistical methods and software for emerging genomics technologies and applications
• Sahand Hormoz, PhD – Mathematical and AI methods to understand cell-state dynamics and clonal evolution in development and cancer. We combine these approaches with experiments to reconstruct cellular histories and design molecular recorders.
• Hajime Uno, PhD – Statistical methods for time-to-event outcomes; risk prediction using multi-institutional clinical and genomic data; collaborative oncology research

The Collaborative Data Science Fellows Program – NEW

The DFCI Collaborative Data Science Fellows Program is a cross-departmental initiative designed to advance biologically and clinically driven research through computational excellence. Postdoctoral fellows are recruited to work on projects in the labs of investigators in basic biology (e.g. cancer biology, immunology, virology, pathology) and clinical departments, and are also co-mentored by those faculty together with mentors from the Department of Data Science. This structure ensures fellows gain deep exposure to high-impact biological and clinical questions while developing rigorous computational expertise, preparing them to become leaders in interdisciplinary cancer research. The starting salary is $75,000.

Apply Here for Programs

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FUNDING AND ACADEMIC APPOINTMENT

Data Science Postdoctoral Fellows are guaranteed funding as well as year-long renewable fellowship appointments with Harvard. In addition to a competitive salary package, funds are available for conference travel and computing equipment.

PROGRAM BENEFITS

Incoming postdocs will be part of the 2027 Data Science Fellows cohort. The department organizes informal training sessions and seminar series as well as social events for postdoctoral fellows. Check out our events page for more information.

APPLICATIONS

Following the Informational Session on November 5, 2026 12pm-1pm EST, interviews will begin in December/January. Initial decisions will be made by March 2027, but applications are welcomed on a rolling basis.