Doctoral Student - Neuro-AI lab

About Us: The Technion Neuro-AI Lab is at the forefront of research into the computational mechanisms of biological and artificial neural networks. Our diverse projects range from developing Brain-Computer Interfaces (BCIs) for both rodents and humans to creating theoretical and computational models of neural activity, and training cutting-edge machine-learning models, including large language models (LLMs).

University Environment: Join us at Technion, where we offer a world-class research environment equipped with state-of-the-art facilities and interdisciplinary training programs. The lab is part of the Technion AI community (ranked 1st in Europe) and the (nobel prize winning) Medical faculty. There is a vibrant community and the Lab strongly encourages international mobility, supporting students in undertaking internships and research collaborations abroad.

Lab Homepage: Technion Neuro-AI Lab

Project Descriptions & Candidate Profiles: We are seeking candidates with computational/theoretical or experimental expertise in the following areas:

• Computational Projects:

- Focus: Machine learning, artificial intelligence, and training of various network algorithms.

- Relevant Backgrounds: Computer Science, Electrical Engineering, Data Science, etc.

• Theoretical Projects:

- Focus: Developing theoretical and computational predictions for neural experiments.

- Relevant Backgrounds: Physics, Mathematics, Applied Mathematics, Computer Science, etc.

• Experimental Collaborations:

- Focus: Developing experimental setups with advanced computational tools for BCIs in collaboration with partner labs.

- Relevant Backgrounds: Neuroscience, Biology, Medicine, etc., with strong computational skills.

What We Offer:

• A stimulating and supportive research environment.
• Access to state-of-the-art equipment and infrastructure.
• Opportunities for interdisciplinary scientific development.
• An international and collaborative team atmosphere.
• Comprehensive training in a wide range of scientific skills.
• Opportunities to present your research at international conferences and workshops.
• Extensive support for career development beyond your Ph.D.

Application Deadline: We encourage candidates to apply as soon as possible. Our goal is to fill positions by Spring 2025.

How to Apply: Please send your CV and full academic transcript directly to Prof. Stefano Recanatesi ([email protected]).