"Postdoctoral Position in Database Systems"

We invite applications for a postdoctoral position in database systems with a strong theoretical foundation. We are looking for a candidate excited by the challenge of rethinking data systems in the face of modern constraints such as optimization under uncertainty, constrained query evaluation, or the design of efficient, explainable, and scalable query engines.

The successful applicant will help design and build novel systems and algorithms that challenge traditional assumptions in databases, guided by both real-world needs and formal foundations. They will work at the intersection of systems and algorithms, in collaboration with faculty, students, and external partners.

Key Responsibilities

• Lead independent and collaborative research on topics in database systems, including constrained query evaluation, optimization, and reasoning under uncertainty.
• Design and analyze novel algorithms or theoretical models related to modern data management challenges (e.g., query feasibility, data correlations, probabilistic evaluation, scalability).
• Prototype and evaluate data system components or extensions to existing open-source engines.
• Publish in top-tier conferences (SIGMOD, VLDB, PODS, ICDE, ICDT, etc.) and participate in the wider research community.
• Mentor students and contribute to a vibrant research culture at NYUAD.
• Participate in cross-disciplinary projects at CITIES, connecting data systems to applications in urban science, planning, and decision support.

Qualifications Required:

PhD in Computer Science or a related field, with a focus in databases, data systems, theory, or algorithms. Strong publication record in top-tier venues.

Solid background in one or more of the following:

• Query processing or optimization
• Constrained or combinatorial query evaluation
• Data modeling under uncertainty or imprecision
• Design and implementation of database or data analysis systems
• Excellent programming and prototyping skills.
• Strong analytical and communication skills; ability to work both independently and collaboratively.

Desirable:

• Familiarity with modern in-process or embedded query engines (e.g., DuckDB, SQLite, etc.)
• Experience working with probabilistic databases, provenance, or uncertain data
• Exposure to decision-making, multi-objective optimization, or declarative problem modeling
• Prior involvement in open-source or reproducible systems research
• Interest in interdisciplinary applications of data systems (e.g., urban analytics, scientific workflows)

For consideration, applicants need to submit a cover letter, curriculum vitae with full publication list, degree transcript, statement of research interests, and at least two letters of reference, all in PDF format. If you have any questions, please email Azza Abouzied - aa175@nyu.edu