PhD Student – AI Applied Researcher

Job Description
GM Israel (Herzliya)
takes a significant part in introducing sophisticated software features into car in many domains like connected cars, advanced camera technologies and research. We shape the face of the future vehicles in diverse fields by developing cutting edge technologies. GM is committed to Zero Emission, Zero Crashes and Zero Congestion vision.

About the Group:
General Motors R&D Lab in Israel is an applied research center focusing on creating and evaluating innovations for future vehicles. Our researchers conduct independent technical work, while initiating and leading collaborative projects with colleagues at academia and industry, both in Israel and globally.

As a member of General Motors Research Labs, the Vehicle Controls group offers exciting opportunities for motivated researchers with outstanding capabilities to conduct research in applied AI for developing cutting edge, world changing technologies for GM's future vehicles.

We are seeking for a
highly motivated and talented PhD student
to join our team.

What You Will Do
As a part of the Research team, you will join a leading applied AI research team. You will develop AI/RL technologies that will change the future of mobility. You will collaborate with world-class universities / industry partners while publishing research outcomes internally and externally. Broader research areas include:

• Explore, invent, innovate, implement, evaluate and test algorithms as an independent yet integral member of a research team
• Identify research gaps, propose, plan and execute complex research projects
• Maintain state-of-the-art technical expertise in AI/RL
• Generate intellectual property, document results and publish papers
• Demonstrate strong interpersonal skills and ability to work in a team environment including cross-functional global teams

Your Skills & Abilities (Required Qualifications)

• A PhD student in AI, reinforcement learning, computer science, engineering, physics, or a related field.
• Proven expertise in one or more of the following areas: deep learning, autonomous agents, large-scale multi-agent systems, prediction, distributed optimization, or reinforcement learning.
• Experience handling large-scale, high-dimensional data from diverse sources using advanced machine learning techniques.
• Demonstrated ability to prototype algorithms, as well as implement and test software on hardware platforms.
• Strong programming skills in Python and familiarity with common AI/ML frameworks (e.g., PyTorch, TensorFlow, sklearn, etc.). Hands-on experience is essential.
• Industrial experience – a significant advantage.

About GM
Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all.

Why Join Us
We believe we all must make a choice every day – individually and collectively – to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team.

Non-Discrimination and Equal Employment Opportunities
General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers.

We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required, where applicable, to successfully complete a role-related assessment(s) and/or a pre-employment screening prior to beginning employment. To learn more, visit
How we Hire
.

Accommodations
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email
us or call us at In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying.