Mathematical Exploratory Science - MSc and PHD-Summer internship 2025- Research Lab
IBM
At IBM, work is more than a job - it's a calling: To build. To design. To code. To consult. To think along with clients and sell. To make markets. To invent. To collaborate. Not just to do something better, but to attempt things you've never thought possible. Are you ready to lead in this new era of technology and solve some of the world's most challenging problems? If so, lets talk.
Do you want to work with top researchers at the intersection of Generative AI and combinatorial optimization?
The Mathematics of Decision-Making team at IBM Research is looking for an outstanding advanced degree student (M.Sc. or Ph.d.) for a summer internship position to drive forward the state-of-the-art research in the above areas.
You will enjoy working with us if you are passionate about carrying out leading edge scientific research with application to real world problems, and love working with a team of researchers who are leaders in their fields.
Responsibilities
- Design and develop complex models, architectures, and algorithms at the intersection of Generative AI (including Large Language Models) and optimization.
- Prove theoretical results in these areas.
- Design, implement and analyze empirical experiments intended to test the algorithms.
- Demonstrate scientific eminence by publishing the results of your work in leading scientific journals and conferences and by filing patents.
- Advocate for your ideas and collaborate with other research scientists and engineers to design the best solution.
- Possible application of work to real world business scenarios.
Locations:
- IBM Research Lab, Israel (Haifa University Campus)
- IBM Site, Hashahar Tower, Givataim (near Tel Aviv Arlozorov train station)
- Studying towards an advanced degree (M.Sc. or Ph.D.) in Applied Mathematics, Computer Science, Operations Research, or other related scientific discipline.
- Strong background in Generative AI, particularly transformers, Graph Neural Networks and or Large Language models.
- Strong background in mathematical optimization.
- Demonstrated ability in proving theoretical results, and/or designing, implementing, and analyzing numerical experiments.
- Working proficiency in Python.
- Good communication skills and ability to work in a collaborative team environment.
- Preferably, strong background in computational complexity.
Please add your grade sheet to your application