Home » Research » Opportunities » Fully-funded Ph.D. student position(s) in analysis and transformations of Deep Learning programs in New York City

Recent News




Fully-funded Ph.D. student position(s) in analysis and transformations of Deep Learning programs in New York City

I am currently seeking (potentially multiple, fully-funded) Ph.D. students interested in programming languages and software engineering research for an NSF-funded project on analysis and transformations for (imperative) Deep Learning (DL) programs. The project—based in the heart of New York City—focuses on enhancing the robustness, increasing run-time performance, and facilitating the long-lived evolution of DL systems, particularly, large, industrial DL systems. For more information on the project, please see the project announcement.

Potential research topics explored during the course of the project may include (static/dynamic) program analysis and transformation (e.g., automated refactoring) and empirical software engineering. Successful candidates will be expected to work on projects that generally yield open-source developer tool research prototypes, plug-ins to popular IDEs, build systems, or static analyzers. Applicants may find additional information on the PI’s web page. They should also apply to the City University of New York (CUNY) Graduate Center (GC) Ph.D. program in Computer Science (deadline December 15) following a discussion with the PI.

Please see below for additional details on applying. Again, the Ph.D. program deadline is December 15.

Topics of Interest

  • Static code analysis
  • Dynamic code analysis
  • Deep Neural Networks
  • Program transformation
  • Automated refactoring
  • Software evolution
  • Empirical software engineering


programming languages, software engineering, automated refactoring, static analysis, dynamic analysis, IDEs, developer tools, software evolution, deep learning, imperative programs, hybrid programming paradigms, empirical studies


Shared lab space will be available to successful candidates at the City University of New York (CUNY) Hunter College Computer Science Department, New York, NY, USA.


The Ph.D. studentship is fully-funded. CUNY provides competitive funding packages. Potential applicants may find funding information on the CUNY GC website.

Start Date

August 2022.


Raffi Khatchadourian, principal supervisor. More info on this web page.

Expected Skills and Qualifications

Successful candidates will have earned either a BS or MSc degree (or equivalent) in Computer Science or a related field. A successful candidate will have a solid practical and theoretical background in the following areas. Note, however, possessing all such skills does not necessarily disqualify applicants:

  • AI, Machine Learning, Deep Learning, analytics, and data mining.
  • (Object-Oriented) programming languages.
  • (Front-end) compilers.
  • Data structures.
  • Algorithms.
  • Software design patterns.
  • Software testing.
  • Software engineering tools, e.g., IDEs, build systems, version control.
  • Data mining, software repository mining (MSR).
  • Empirical software engineering.

Successful candidates may also have the following:

  • A strong mathematical logic, statistical, and set-theoretic foundation.
  • Industrial experience.
  • Software engineering skills.
  • High-quality analytical skills.
  • Experience in developer tool design and implementation, relational databases, and statistical software (e.g., R, spreadsheets).


Please complete the following form. Please note that partial form submissions can be saved for later completion.

The City University of New York – CUNY’s Graduate Center Ph.D. program in Computer Science information and requirements regarding admission is available here. Note the deadline for Dec 15.The Computer Science program requirements are listed here. Also note that the college program requirements may include a GRE. International students are encouraged to visit this web page for more information regarding international requirements.

"*" indicates required fields

MM slash DD slash YYYY
Please enter a preferred start date if you do not plan to start in Fall 2023.
Do you require sponsorship?*
For international students.
What will be your highest educational degree achieved by the start date?*

Accepted file types: pdf, Max. file size: 128 MB.
Accepted file types: pdf, Max. file size: 128 MB.
Please include projects and courses that could be related to the subject.
Drop files here or
Accepted file types: pdf, Max. file size: 10 MB.
    From Bachelor to MSc if applicable.
    Please provide two to three professional references.*
    These people should be familiar with your work. Please inform your references beforehand that they may be contacted regarding your application.

    Leave a Reply

    This site uses Akismet to reduce spam. Learn how your comment data is processed.

    %d bloggers like this:
    Need help with the Commons? Visit our
    help page
    Send us a message