# The Quantitative Biological Systems Training (QBIST) Program

> **NIH NIH T32** · NEW YORK UNIVERSITY · 2024 · $439,487

## Abstract

Abstract / Summary
The widespread adoption of genome-scale methods in biomedical research has resulted in biology now being
a big data discipline that requires training in modern machine learning and artificial intelligence (AI). Formal
instruction in both biology and AI is critical for PhD trainees pursuing careers in a broad range of academic and
non-academic fields. The mission of the Quantitative Biological Systems Training (QBIST) program is to
empower biomedical researchers to choose confidently amongst a diversity of careers through active training
and experiential learning in robust and transferable quantitative and leadership skills. The second award period
of the QBIST program will focus on 3 primary objectives. Objective 1: Consolidate training opportunities to
develop and apply advanced computational and data science skills to complex biomedical research
questions. We will modify the QBIST curriculum to respond to the evolving demands of quantitative training to
ensure training in cutting edge methods. Objective 2: Enhance the value of mechanisms for exploring
biomedical career paths outside the traditional academic trajectory. QBIST trainees will continue to
explore post-graduate career options through participation in an internship program with non-academic
organizations. In addition, we will provide opportunities to participate in established entrepreneurial and
multi-dimensional team-building programs at NYU to expand training options. We will also increase the value
of these experiences by providing opportunities for self-reflection. Objective 3. Provide trainees with
opportunities to develop leadership skills through mentoring experience. To enable trainees to gain
critical leadership and mentoring skills in the context of supporting diversity, equity, and inclusion, trainees will
assume mentorship roles in the NYU Biology Summer Undergraduate Research Program. Importantly, we will
modify the existing QBIST curriculum so as to not increase trainee workload to ensure we meet our overall
objective of decreasing time to graduation while maintaining a high PhD graduation rate. The second
award period of the QBIST program will include 17 faculty members at all career stages with a demonstrated
track record of mentoring and commitment to the goals of the QBIST program. To accommodate the expanded
aims of the QBIST program we will select 4 students per year who will be appointed for two years during the
second and third years of their PhD training. Students will be selected by the QBIST program executive
committee on the basis of a written application detailing training goals and long-term career objectives that
demonstrate alignment with the QBIST program. To assess the continued effectiveness of the QBIST program,
we will use annual surveys completed each year by all trainees and quantify trainee research and career
outcomes. All data and analyses will be made publically available on the QBIST web portal. Achieving the
QBIST program ...

## Key facts

- **NIH application ID:** 10849330
- **Project number:** 2T32GM132037-06
- **Recipient organization:** NEW YORK UNIVERSITY
- **Principal Investigator:** David Gresham
- **Activity code:** T32 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $439,487
- **Award type:** 2
- **Project period:** 2019-07-01 → 2029-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10849330

## Citation

> US National Institutes of Health, RePORTER application 10849330, The Quantitative Biological Systems Training (QBIST) Program (2T32GM132037-06). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10849330. Licensed CC0.

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