Postdoctoral researcher in natural language processing and real-world data

Join our team of data scientists and infectious disease epidemiologists to develop and validate language technology models for analyzing real-world data from general practitioners, with a focus on infections and post-infectious symptoms. Every day, we strive to improve healthcare and the health of people. We offer good employment conditions and value your continuous personal and professional development.

Job Description

At the Julius Center for Health Sciences and Primary Care, a key research area is the relationship between acute infections and non-communicable diseases (e.g., cardiovascular, auto-immune), using large-scale real-world data. This PostDoc position is part of a ZonMw-funded project investigating long-term risks in patients with post-COVID compared to individuals with similar complaints after other viral infections.

As a post-doctoral researcher, you will work at the intersection of data science, epidemiology, and clinical research, developing innovative methods to optimize the use of rich real-world data. You will be part of a collaborative, interdisciplinary team of motivated data scientists, clinicians, and epidemiologists. Your main focus will be developing and validating Natural Language Processing (NLP) models to extract clinically meaningful diagnoses, symptoms, signs, and disease durations linked to infections and post-infection syndromes, including post-COVID. You will work with extensive real-world data from general practitioners to extract clinically relevant information and contribute to innovative solutions in infectious disease research.

Beyond model development, you will have the freedom to work on improving the generalizability and robustness of these models by exploring different modelling techniques, evaluating the impact of design choices, and addressing common pitfalls in model interpretation with implications for real-world clinical and epidemiological research.

Work Environment

The Julius Center for Health Sciences and Primary Care is part of the University Medical Center Utrecht. It conducts scientific research, provides education, and offers expertise and facilities in clinical health sciences and public health. Within the Julius Center, the interdisciplinary department of Epidemiology of Infectious Diseases is a collaborative team of full, associate, and assistant professors, along with PhD students. Together, we conduct research, provide education, and offer expert advice on the prevention, diagnosis, prognosis, and treatment of infectious diseases, with a focus on hospital-acquired respiratory infections. The program, led by Prof. Dr. Patricia Bruijning-Verhagen, applies advanced epidemiological and statistical methods, including multicentre randomized trials of preventive and therapeutic interventions, as well as population-based studies and analyses using real-world data.

Requirements

• Completed a university master's degree in computer science, computational linguistics, AI, engineering, bioinformatics, or a comparable technical study, and obtained a Ph.D. in a relevant area (or dissertation completed, pending defense).
• Experience in healthcare data research is an advantage.
• Strong interest in scientific research.
• Skilled in Python (experience with NLP/ML libraries, e.g., PyTorch, is a plus).
• Excellent written and spoken communication skills in English, and preferably Dutch. Excellent communication and organizational skills.
• Analytical, creative, curious, and results-oriented.
• Enjoy working both independently and collaboratively in an interdisciplinary team.