The project will further the field of physician-in-the-loop healthcare model development by exploring novel clinical knowledge graph architectures and novel use of graph structure in predictive models and will also develop AI/ML models to improve medical care for pediatric patients across a broad array of subspecialties. The project will target publications in leading machine learning/AI venues and top medical and medical informatics journals. 

The successful candidate will primarily research machine learning models using knowledge graphs and high-dimensionality electronic health record (EHR) data sets including tables, free text, clinical images, and scanned images of free text. We are particularly interested in individuals with a strong background in AI, ML, deep learning, large-scale machine learning systems, and knowledge graph models, who are excited about applying their AI/ML skills to challenges in healthcare. 

Responsibilities: 

• Develop and apply machine learning models for the analysis of risk factors for a variety of pediatric conditions and/or predict their incidence and progression 
• Develop novel knowledge graph architectures or applications of knowledge graphs that optimize the use of clinical relational knowledge in predictive models for high performance and explainability 
• Publish their works in top computer science conferences and high-impact medical and general scientific journals 
• Work collaboratively with a multidisciplinary team to understand clinical needs and translate them into algorithmic solutions 

Qualifications: 

• A Ph.D. in Computer Science or a related field 
• Strong publication records in the related area of ML, AI, and NLP 
• Strong programming skills in Python and libraries such as PyTorch 
• Experience in healthcare AI/ML and graph theory is highly desired 
• Excellent problem-solving skills, independent thought, and the ability to manage multiple projects 

We offer a competitive salary and benefits package and the opportunity to work in a supportive, interdisciplinary environment. The postdoc will have the opportunity to work closely with both professors and their teams and will be encouraged to develop their independent research ideas. 

Candidates should submit a CV, a statement of research interests, two representative publications, and contact information for three references to arcross@uic.edu and jimeng.sun@gmail.com. Applications will be reviewed on a rolling basis until the position is filled. 

The University of Illinois College of Medicine Peoria and the University of Illinois Urbana-Champaign are equal opportunity employers and encourage applications from underrepresented minorities and women. 

Dr. Adam Cross, 

Director, Children’s Innovation Lab 

Children’s Hospital of Illinois (CHOI) 

Department of Pediatrics, University of Illinois College of Medicine Peoria

Dr. Jimeng Sun, 

Health Innovation Professor 

at Computer Science Department and Carle Illinois College of Medicine, University of Illinois Urbana-Champaign