Are you passionate about building practical tools for developers, improving AI integration into the software development cycle, or advancing the capabilities of program analysis? Join us at the SANAD Lab at NYU Abu Dhabi for a fully funded PhD in Software Engineering.
We are seeking motivated PhD students to join our research team, co-led by Sarah Nadi and Karim Ali. The SANAD Lab (Software Analysis and Developer Support) focuses on building scalable, precise, and actionable tools that improve how developers write, understand, and maintain software. PhD students will be supervised by Sarah or Karim, or can opt for joint co-supervision.
Our Current Research Themes
PhD students will have the opportunity to contribute to and shape projects in areas such as:
- Dependency management and software supply chain (e.g., API version updates, library migration, API misuse)
- Assessing and improving correctness of LLM-generated code
- Smart contract security
- Software energy efficiency
- AI for Software Engineering
- Program analysis for detecting security vulnerabilities
- Scalable and precise pointer analysis
Why Join SANAD?
- A collaborative research group with access to state-of-the-art computing resources
- A track record of publications at top venues (ICSE, FSE, ASE, ICSME, TSE, MSR, EMSE, OOPSLA, ISSTA, etc.)
- Opportunities for mentorship, international collaboration, and research visits
- Generous funding package
- Living in one of the safest and sought after cities in the world, Abu Dhabi, and working in our beautiful Saadiyat campus
About the Position
- Location: NYU Abu Dhabi (UAE)
- Start Date: Fall 2027
- Duration: 4 years (full-time, funded)
- Supervisors: Sarah Nadi and/or Karim Ali
- Application Deadline: December 12, 2026. Please apply to NYU, making sure that you select Campus preferences that include Abu Dhabi (i.e., Abu Dhabi 1st and Abu Dhabi 2nd).
Ideal Candidate
- A strong background in software engineering, programming languages, or security
- Experience in static/dynamic analysis, mining software repositories, or AI for code is a plus
- Proficient in Python, Java, Swift, Scala, or C/C++
- Demonstrated research potential (e.g., thesis, publications, open-source contributions)
- Ability to communicate ideas and results clearly, in writing and in person
How We Work (and Who Thrives Here)
Technical skill gets you in the door, but members who do their best work with us tend to share a particular way of approaching research. If the following resonates with you, you’ll fit in well:
- Intellectual honesty above all. We care more about what is true than what is impressive. A negative result you can trust is worth more than a positive result you can’t, and “I’m not sure yet” is always a better answer than a confident guess. We would rather hear that an experiment failed than see it dressed up.
- A reproducibility reflex. You pin your versions, script your experiments so someone else can re-run them, and sanity-check your own numbers before you present them. If a result can’t be reproduced, we treat it as not yet real.
- You follow the evidence, even when it’s inconvenient. You are willing to let the data overturn a hypothesis you’re attached to, and to recognize when the thing that “didn’t work” is actually the most interesting finding in the project.
- You see problems through. Research has long, unglamorous stretches: debugging a toolchain, getting a harness to run end to end, chasing down the last few percent that won’t replicate. We value people who own a problem from its messy start to a finished result, rather than handing it off when it stops being fun.
- You take feedback well and give it honestly. Our drafts come back heavily marked up. That’s a sign of investment, not disapproval. You can defend an idea, change your mind when the argument is better, and offer the same direct, respectful critique to your collaborators.
- You write with care. Clear writing reflects clear thinking. You don’t need to arrive a polished writer, but you should want to become one and take editing seriously.
- You are curious and self-directed. You read beyond what’s assigned, keep up with the literature, and bring your own ideas to the table, while knowing when to ask for help instead of staying stuck.
- You’re a good lab citizen. You’re reliable, you communicate early when a plan slips, and you make the people around you better.
How to Indicate your Interest in this Position
Submit an application to our internal lab application system. Please indicate whether you’re particularly interested in working with Dr. Nadi, Dr. Ali, or are interested in co-supervision. Note that this does NOT replace the need to apply to NYU’s application system above. This is a way to indicate your interest to us without directly emailing us.