HAL faculty view analytics as the translational arm of data science — a powerful tool for explaining, predicting and ultimately enhancing our understanding of human behavior in organizational and technological contexts. HAL integrates computer science, statistics, psychology, and information systems into a cohesive approach. This "T-shaped" structure features broad theoretical foundations with deep methodological expertise. HAL faculty develop and apply rigorous analytical methods to frame, evaluate and solve real-world problems. Led by two endowed chairs in analytics from different specializations, HAL transcends traditional disciplinary boundaries. The business school foundation of the Lab ensures research remains pragmatic and applicable, treating the world as a laboratory while maintaining methodological rigor.

The Fellow will reflect HAL’s view of the role of analytics - as the translational arm of more foundational areas of data science, merging multiple fields into an interdisciplinary integration of technology, psychology, methodology, and relevant application domains. The Fellow will support and lead on-going HAL research projects related to the use of machine learning and large language models (LLMs) for multi-modal health analytics in real-world settings such as social robots for the elderly and mental health assessments. Ideal candidates will have research interests, computational and technical skills, and prior experience at the intersection of machine learning/LLMs, processing and analyzing unstructured user-generated text/sensor data, and responsible AI.    

The position, supervised by HAL Faculty Co-Directors Ahmed Abbasi and Ken Kelley, is for 1 year with potential for a second year), with the anticipated start date being as soon as the position is filled . The Fellow will actively participate in the intellectual community of HAL, making progress on the aforementioned health analytics research projects, their own research, assisting with PhD student mentoring, and submitting research for publication in top journals. The position includes a travel allowance for collaborations and conference presentations. This is an in-person position at the University of Notre Dame campus in South Bend, Indiana.

Qualifications:
- PhD in Computer Science, Data Science, Information Systems, Statistics, Computational/Quantitative Psychology, or related fields  
- Track record  of publications and/or desire to publish in top conferences or journals (i.e., publications and working papers).
- Proficiency in Python for data wrangling, machine learning packages such as Scikit learn, Tensorflow, PyTorch, Transformers, etc.  
Experience with open-source software and reproducible research (e.g., GitHub repos), including with LLMs.
- Ability to develop manuscripts, research reports,and  weekly updates in laTex platforms such as Overleaf
Application Requirements:
- Updated CV, indicating date of PhD completion, publications and working papers, technical skills, software packages developed, or open code repositories, etc.
- A brief cover letter.
- Two letters of recommendation highlighting the candidate’s research accomplishments.

Applications will be reviewed on a rolling basis between now and December 15th.

Learn more and apply: apply.interfolio.com/172741