Postdoctoral Research Opportunity at the University of Notre Dame

University of Notre Dame

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Description

The University of Notre Dame, Indiana, is inviting applications for a Postdoctoral Researcher in the Foundation Models and Applications Lab (FMAL). The lab is led by Associate Professor Meng Jiang, a recognized expert in AI and data science. This position provides an opportunity to conduct pioneering research in foundation models and applications. The role will focus on advancing large-scale AI methods, multimodal learning, and trustworthy systems. It offers a chance to explore how foundation models can address scientific, engineering, and societal challenges. Successful candidates will collaborate with faculty, graduate students, and interdisciplinary researchers. They will also contribute to the development of algorithms, tools, and experimental frameworks. The position emphasizes publishing in top-tier AI and data science venues. Applicants should hold a PhD in computer science, AI/ML, or a closely related field. This is a unique opportunity to shape the future of responsible and impactful AI research. 

Responsibilities

Key Responsibilities

• Conduct innovative research in foundation models and applications: You will drive original investigations into the design, training, and deployment of foundation models, exploring their applications in natural language processing, multimodal AI, and real-world problem-solving. This includes pushing the boundaries of how large-scale models can generate knowledge, adapt to diverse domains, and support scientific and societal progress.
• Develop algorithms, methods, and tools to enhance large-scale AI systems: Your role will involve building novel machine learning algorithms and computational frameworks that improve the scalability, efficiency, and trustworthiness of foundation models. This includes creating software tools and pipelines that make AI systems more robust, interpretable, and accessible for both research and application.
• Collaborate with faculty, researchers, and graduate students on interdisciplinary projects: You will work closely with experts across AI, data science, engineering, and applied sciences, ensuring that your research is not only theoretically strong but also practically impactful. By contributing to team-based projects, you will help bridge AI research with applications in healthcare, climate science, social good, and beyond.
• Lead publications in top-tier AI/ML and data science venues: You are expected to prepare and publish high-quality research in internationally recognized journals and conferences such as NeurIPS, ICML, ACL, AAAI, and KDD. This responsibility highlights your role as a thought leader in the field, ensuring visibility and academic recognition for both your work and the lab’s contributions.
• Mentor and support graduate and undergraduate research assistants: In addition to your independent research, you will provide guidance and mentorship to students, helping them develop technical skills, research maturity, and academic writing abilities. This includes offering feedback on their projects, co-authoring papers, and fostering a collaborative lab culture. 

Qualification

Candidate Profile

1. A PhD in Computer Science, AI/ML, Data Science, or related fields: Applicants should hold a doctoral degree in a relevant discipline, equipping them with advanced knowledge of artificial intelligence, machine learning, or data-driven methods. A strong theoretical foundation and practical expertise will enable candidates to conduct high-impact research in foundation models and their applications.
2. Strong research background in foundation models, NLP, multimodal AI, or machine learning: Candidates must demonstrate in-depth expertise in at least one of these domains, with the ability to design, train, and evaluate advanced AI systems. Familiarity with foundation models, large-scale natural language processing, multimodal learning, or applied ML will be highly valued, especially when combined with curiosity to explore new research directions.
3. Demonstrated publication record in leading AI conferences/journals: An excellent track record of publishing in respected venues such as NeurIPS, ICML, ACL, KDD, or AAAI will be an indicator of the candidate’s ability to produce high-quality, peer-reviewed research. This showcases not only academic excellence but also the ability to communicate ideas to the broader AI/ML community.
4. Excellent programming, data analysis, and problem-solving skills: Applicants should be proficient in programming languages such as Python, along with strong skills in frameworks like PyTorch or TensorFlow. The ability to analyze complex datasets, design efficient experiments, and troubleshoot challenges in large-scale AI systems will be essential for success in this role.
5. Ability to work collaboratively in a multidisciplinary environment: Since the FMAL thrives on cross-disciplinary partnerships, the candidate should demonstrate teamwork, communication, and adaptability. They must be comfortable working alongside computer scientists, engineers, domain experts, and students to ensure research outcomes are both academically rigorous and practically relevant. 

Why join there?

• Cutting-edge research environment: Work at the forefront of artificial intelligence and foundation models, contributing to breakthroughs that shape the future of AI.
• Global academic impact: Collaborate with world-class researchers and publish in top-tier AI/ML conferences and journals, enhancing your academic visibility.
• Interdisciplinary collaboration: Engage with experts across computer science, data science, engineering, and applied domains, expanding both your research scope and career opportunities.
• State-of-the-art resources: Access Notre Dame’s advanced computational infrastructure, research facilities, and support systems to accelerate your projects.
• Mentorship and career development: Receive personalized guidance from Associate Professor Meng Jiang and senior faculty while gaining experience in supervising students and managing projects.
• Supportive community: Be part of a vibrant, inclusive, and collaborative academic environment that values innovation, integrity, and teamwork.
• Real-world applications: Contribute to impactful projects where AI is applied to solve pressing challenges in science, engineering, and society. 

Application Process

Interested candidates are invited to apply through Interfolio at https://apply.interfolio.com/173333

Applications should include the following materials:

1. A Cover Letter outlining your research interests, motivation for the position, and alignment with FMAL’s focus.
2. Curriculum Vitae (CV) detailing academic qualifications, research experience, publications, and technical skills.
3. Research Statement (2–3 pages) highlighting past contributions, current projects, and future research plans.
4. Contact Information for References (at least 2–3 referees who can provide strong academic/research recommendations).

Applications will be reviewed on a rolling basis until the position is filled. Shortlisted candidates may be invited for interviews, including a research presentation and discussion with the lab team.

For questions about the role, candidates may directly contact Associate Professor Meng Jiang at mjiang2@nd.edu & Dr. Xiangliang Zhang at xzhang33@nd.edu, the University of Notre Dame.