https://www.linkedin.com/posts/jannikwiedenhaupt_%3F%3F%3F%3F%3F-%3F%3F-%3F%3F%3F%3F%3F%3F-%3F%3F-%3F%3F%3F%3F%3F%3F-ugcPost-7140914457609662464-E9ud?utm_source=share&utm_medium=member_android
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Jannik Wiedenhaupt on LinkedIn: 𝗪𝗵𝗲𝗿𝗲 𝗶𝘀 𝗚𝗲𝗿𝗺𝗮𝗻 𝗔𝗜 𝘁𝗮𝗹𝗲𝗻𝘁 𝗰𝗼𝗺𝗶𝗻𝗴 𝗳𝗿𝗼𝗺… | 144 comments
𝗪𝗵𝗲𝗿𝗲 𝗶𝘀 𝗚𝗲𝗿𝗺𝗮𝗻 𝗔𝗜 𝘁𝗮𝗹𝗲𝗻𝘁 𝗰𝗼𝗺𝗶𝗻𝗴 𝗳𝗿𝗼𝗺 𝗮𝗻𝗱 𝗴𝗼𝗶𝗻𝗴?
Germany has an amazing education system and great (almost free)… | 144 comments on LinkedIn
Germany has an amazing education system and great (almost free)… | 144 comments on LinkedIn
Position: Funded PhD Position in Optimal Transport Theory for Safe and Robust Multi-Agent Systems
Institution: Center for Human-aware AI (CHAI), Rochester Institute of Technology (RIT)
Location: Rochester, NY, USA
Overview:
The Center for Human-aware Artificial Intelligence (CHAI) at the Rochester Institute of Technology (RIT) is seeking a dedicated PhD student for research at the intersection of optimal transport theory and multi-agent RL. This position aims to develop frameworks that leverage mathematical insights from optimal transport to enhance the safety and robustness of multi-agent RL.
Qualifications:
- Strong background in mathematics or reinforcement learning, evidenced by a Bachelor's or Master's degree in Computer Science, Mathematics, Artificial Intelligence, or related fields.
- Strong programming skills, with proficiency in Python, C++, or similar languages, and experience with RL / multi-agent RL.
Application Process:
Interested candidates are encouraged to contact Dr. Ali Baheri (akbeme@rit.edu).
✔️ @ApplyTime
Institution: Center for Human-aware AI (CHAI), Rochester Institute of Technology (RIT)
Location: Rochester, NY, USA
Overview:
The Center for Human-aware Artificial Intelligence (CHAI) at the Rochester Institute of Technology (RIT) is seeking a dedicated PhD student for research at the intersection of optimal transport theory and multi-agent RL. This position aims to develop frameworks that leverage mathematical insights from optimal transport to enhance the safety and robustness of multi-agent RL.
Qualifications:
- Strong background in mathematics or reinforcement learning, evidenced by a Bachelor's or Master's degree in Computer Science, Mathematics, Artificial Intelligence, or related fields.
- Strong programming skills, with proficiency in Python, C++, or similar languages, and experience with RL / multi-agent RL.
Application Process:
Interested candidates are encouraged to contact Dr. Ali Baheri (akbeme@rit.edu).
✔️ @ApplyTime