# Institutional Career Development Core

> **NIH NIH KL2** · UNIV OF MASSACHUSETTS MED SCH WORCESTER · 2022 · $635,999

## Abstract

Our KL2 program seeks to develop the careers of 3 highly qualified scholars (junior faculty) at any given time.
The goal is that scholars become translational scientists who will possess both the fundamental NCATS 
competencies and 7 essential characteristics that will enable them to become transformational agents of change
across the translational research spectrum. These 7 characteristics are: boundary crosser, team player, 
process innovator, domain expert, rigorous researcher, skilled communicator, and systems thinker. We will 
accomplish this by offering mentoring via a transdisciplinary team, a structured curriculum, and multiple 
enrichment opportunities. The typical scholar will have a 2-year tenure, submit an application for extramural funding
as PI, and acquire an MSCI, although PhD level work is also possible, and not all scholars may work towards a
formal degree. Another new feature for this application is a choice of 5 formal pathways (for both degree and
non-degree scholars), 4 of which represent specialization in a translational domain (e.g. data science). The
KL2 is fully integrated into the UMCCTS K program, which is an umbrella program modeled after the KL2 but
adding 3 additional institutionally funded K scholars.

## Key facts

- **NIH application ID:** 10414822
- **Project number:** 5KL2TR001455-07
- **Recipient organization:** UNIV OF MASSACHUSETTS MED SCH WORCESTER
- **Principal Investigator:** CATARINA I. KIEFE
- **Activity code:** KL2 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $635,999
- **Award type:** 5
- **Project period:** 2015-08-14 → 2025-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10414822

## Citation

> US National Institutes of Health, RePORTER application 10414822, Institutional Career Development Core (5KL2TR001455-07). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10414822. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*