Fall 2022 PhD Positions in Explainable Artificial Intelligence at the University of South Carolina

[fago...@uci.edu]

We are looking for PhD students for Fall 2022 who are interested in research in explainable artificial intelligence (XAI) for sequential decision making problems at the University of South Carolina. Our goal is to develop AI algorithms that can learn human-understandable solutions to problems ranging from the Rubik’s cube to chemical synthesis. Furthermore, we are interested in human-AI collaboration, where humans learn from AI and AI learns from humans, for both personalized solutions and for the discovery of new knowledge (https://lnkd.in/gEbq2i3m).

---Research Group---
The research group advisor is Forest Agostinelli (https://lnkd.in/gzydw6YM). Students will also be part of the university-wide AI Institute at the University of South Carolina (https://aiisc.ai/), which promotes interdisciplinary collaboration throughout the university. 

We have ongoing research on topics such as:
- XAI to facilitate human-AI collaboration
- XAI for lifelong learning
- Deep learning and XAI for medical imaging
- Deep learning for physics applications
- Model-based reinforcement learning
- Reinforcement learning and search for chemistry applications
- Deep learning algorithms and theoretical insights for improved accuracy and robustness against adversarial attacks

---Qualifications---
Required
- Bachelor’s or Master’s degree in computer science or a related discipline.
- Strong background in machine learning
- Proficiency in Python
- Proficiency in TensorFlow or PyTorch
- One or more of the following skills: deep learning, reinforcement learning, inductive logic programming

Preferred
- Demonstrated research experience
- A background in a field such as physics, chemistry, biology, or quantum computing.

---Application---
Deadline for Fall 2022 admission: February 1st.
Application link: https://lnkd.in/g4z7FxsM

Interested applicants are encouraged to send the following to for...@cse.sc.edu in a single PDF document:
1) A one-page cover letter describing how your background fits with this research group 
2) CV

3) Transcripts

Best,
Forest
--
Forest Agostinelli
Assistant Professor, 

AI Institute, Department of Computer Science and Engineering

University of South Carolina
https://cse.sc.edu/~foresta/