# Predoctoral Training in Quantitative Neuroscience

> **NIH NIH T32** · CALIFORNIA INSTITUTE OF TECHNOLOGY · 2021 · $293,991

## Abstract

7. Project Summary/Abstract
This proposal will create a program for Predoctoral Training in Quantitative Neurosciences at Caltech. The field
of neuroscience is currently experiencing explosive growth, driven by a plethora of new technologies for
observing and manipulating the brain. To apply these methods fruitfully and interpret the resulting flood of data,
modern neuroscientists need a sophistication in mathematical and computational approaches that traditional
neuroscience training programs cannot provide. At the same time we are seeing a convergence of
understanding at different levels of brain organization, ranging from the molecules that specify neural
connections to the dynamic function of large circuits in the human brain. Thus, there is an urgent need to train
young neuroscientists with an integrated perspective that spans many levels – from molecules to behavior to
computation – which have traditionally been taught in separate programs. Caltech is in an ideal position to
answer these demands. It is an institution almost entirely dedicated to scientific research, routinely ranked
among the top few universities in the world. Caltech is well known for its rigorous training in physics,
mathematics, and engineering, but it also has a distinguished history in biological research, and in the
neurosciences in particular. The small size supports a climate in which scientific collaboration across
disciplines is effortless. The present proposal exploits these institutional strengths to create a new environment
for training in quantitative neuroscience. The program is focused on PhD students in years 1 and 2. The
strategy begins with highly selective recruiting of candidates from a broad range of undergraduate majors,
ranging from biochemistry to psychology to computer science. First-year students get introduced to faculty
research during three rotations of 3 months each, after which they choose a primary mentor to supervise their
PhD research. Trainees also complete a rigorous 2-year course curriculum that ensures core competency in
the following six areas: (i) molecular and cellular neuroscience; (ii) systems and computational neuroscience;
(iii) human neuroscience and brain disorders; (iv) tools and technology for neuroscience; (v) applied
mathematics and statistics; (vi) scientific programming and data analysis. Trainees get writing experience
through a mentored process of fellowship applications. They also give numerous oral presentations in forums
on and off campus. After a candidacy examination at the end of year 2, trainees focus on PhD research, with
the aim of authoring one or more major publications, and graduating by year 6 or earlier. Each trainee's
trajectory through the program is accompanied by individualized advising, adjusting coursework to ensure
broad competency while also challenging the student in a domain of special expertise. In summary, the
proposed program in quantitative neurosciences responds in a timely manner to an urg...

## Key facts

- **NIH application ID:** 10237128
- **Project number:** 5T32NS105595-03
- **Recipient organization:** CALIFORNIA INSTITUTE OF TECHNOLOGY
- **Principal Investigator:** MARKUS MEISTER
- **Activity code:** T32 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $293,991
- **Award type:** 5
- **Project period:** 2019-07-01 → 2024-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10237128

## Citation

> US National Institutes of Health, RePORTER application 10237128, Predoctoral Training in Quantitative Neuroscience (5T32NS105595-03). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10237128. Licensed CC0.

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