Students / GQS PhD Colloquium

GQS PhD
Colloquium

The GQS PhD Colloquium introduces the applications of research in finance for the world’s leading PhD students and postdocs.

Apply Here

Program Overview

The GQS PhD Colloquium is a three-day gathering of the world’s leading PhD students and postdocs who are invited to share their research and exchange ideas with quantitative researchers from Citadel’s Global Quantitative Strategies.

Attendees will also explore the critical applications of deep, rigorous research within GQS, Citadel’s quantitative trading team.

The evenings are reserved for guests to participate in some of New York City’s best dining, entertainment and cultural experiences.

Find Career Opportunities

Participants will meet with GQS quantitative researchers and learn about internship and full-time positions.

Exchange Ideas

Students will be introduced to the cutting-edge work of peers in machine learning, physics, math, and statistics. GQS researchers will share how their PhD backgrounds enable them to work on the latest advancements in quantitative finance.

Enjoy NYC

This all-expenses-paid event includes travel to and from NYC, top tier accommodations, fine dining events, and complimentary tickets to museums, a Broadway show and sports games.

GQS PHD Site

Apply for the
GQS PhD Colloquium

  • Applicants must be PhD students or postdocs
  • While there is no specified graduation year, preference is given to those who are further along in their academic progress

 

Location: In-person, New York City
Dates: April 30-May 3, 2025
Application deadline: April 14, 2025
Selected applicants will be notified on a rolling basis but no later than April 15, 2025.

GQS PHD Site
Apply Here

About Global
Quantitative
Strategies

Founded in 2012, Global Quantitative Strategies (GQS) is Citadel’s quantitative investment strategy. We’ve rapidly grown to become one of the firm’s core investment strategies and one of the top quantitative investment teams in the world.

Our agile teams of researchers, engineers and traders develop robust mathematical models and statistical methods to identify investment opportunities with unparalleled depth, breadth and scale.

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