Hiring
📝 Ready to apply? Submit your details using the Google Form. Email may be missed—form submissions are reviewed regularly.
Join our lab
We are the ARIA Research Lab in the Department of Computer Science at NJIT. We are recruiting Ph.D., MS, and undergraduate students for research positions. Ph.D. positions are fully funded; MS/undergrad students can earn research credit. Self-funded visiting students/scholars are also welcome.
| Â | Â |
|---|---|
| University | NJIT (R1), Newark, NJ |
| Start date | Spring/Fall 2026 |
| Ph.D. funding | RA/TA (2 fully funded positions + self-funded) |
| MS/Undergrad | Research credit available |
Open research projects
| Project | Levels | Summary |
|---|---|---|
| Neurosymbolic AI | Ph.D. lead, MS, undergrad | Integrate symbolic reasoning with deep learning for transparent, interpretable AI systems. |
| Neural combinatorial optimization | Ph.D. lead, MS, undergrad | Build neural solvers for discrete and graph-structured optimization problems. |
| DRL for graph optimization | MS, undergrad | Apply deep reinforcement learning to graph-based combinatorial optimization problems. |
| Applications of neurosymbolic methods | All levels | Apply neurosymbolic methods to vision, video understanding, and multimodal reasoning. |
Who can apply to our lab
Ph.D. students
- We are currently looking for up to 2 funded Ph.D. students (RA/TA) to start in Spring/Fall 2026.
- Strong research background in AI/ML required.
- You must also apply through the NJIT graduate admissions portal and mention our lab in your Statement of Purpose.
MS students
- Research credit via CS 700B (Master’s Project) or CS 701B (Master’s Thesis).
- Exceptional contributors may continue long-term or transition to Ph.D.
Undergraduates
- Research credit via CS 488 (Independent Study).
- Outstanding contributors may extend to full research projects and potential publications.
What you’ll do
- Prototype novel algorithms and run ablations at scale.
- Build reliable, reproducible research pipelines.
- Design experiments, interpret results, and iterate.
- Apply methods to vision/video and multimodal tasks.
- Work on projects that can be submitted to top-tier AI/ML venues.
What you’ll bring
Essential
- Strong ML/AI fundamentals.
- Python + PyTorch/JAX (optionally PyTorch Geometric).
- Background in algorithms and probability.
- Good software practices (git, testing, reproducibility).
Nice to have
- Neurosymbolic AI or symbolic reasoning.
- Combinatorial/constrained optimization.
- Deep reinforcement learning.
- Graphical models and probabilistic circuits.
Lab resources
- Funding: Fully funded Ph.D. (RA/TA), research credit for MS/undergrad.
- Compute: University Wulver GPU cluster + lab GPUs.
- Mentorship: Direct guidance, with opportunities for publications at venues such as NeurIPS, ICML, ICLR, AAAI, KDD, and CIKM.
Why NJIT
- Ranked #72 in the U.S. for AI & Machine Learning (CSRankings).
- Ranked #80 Graduate School for Computer Science (U.S. News & World Report).
- Ranked #84 among National Universities and #42 among Top Public Universities (U.S. News & World Report).
- Located in Newark, NJ—part of the NYC metropolitan area, ~30 minutes from Manhattan with strong industry connections.
FAQ
Q: Should I email you directly?
A: No—please use the Google Form. Emails are often missed, but form submissions are reviewed regularly.
Q: Do I need publications to apply?
A: Not required, but helpful. We value demonstrated research potential and strong fundamentals.
Q: Can international students apply?
A: Yes. Ph.D. positions are fully funded regardless of citizenship.
Q: What’s the application timeline?
A: We review applications on a rolling basis. Apply early for best consideration.
Ready to apply?
Submit your details via the Google Form.
For Ph.D. applications, also apply through NJIT admissions and mention my name in your Statement of Purpose.