Postdoctoral researcher in natural language processing and real-world data

With our team of data scientists and infectious disease epidemiologists, you will develop and validate language technology models to analyse real-world data from general practitioners, focusing on infections and post-infectious symptoms.

Dit ga je doen

At the Julius Center for Health Sciences and Primary care, one of our key research areas 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 on 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 their generalizability and robustness 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.

Hier ga je werken

The Julius Center for Health Sciences and Primary Care is part of the University Medical Center Utrecht. It carries out scientific research, provides education, and offers expertise and facilities in the area of clinical health sciences and public health. Within the Julius Center, our interdisciplinary department, 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. We also 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.

Dit neem je mee

You have completed a university master's degree in computer science, computational linguistics, AI, engineering, bioinformatics or a comparable technical study and have obtained a Ph.D. in a relevant area (or have completed your dissertation, 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.
• You are analytical, creative, curious and results-oriented.
• You enjoy working both independently and collaboratively in an interdisciplinary team.

Dit bieden we jou

• A salary between € 3598 - € 5669 gross per month (salary scale 10), based on full-time employment (36 hours).
• Year-end bonus of 8.3% and holiday allowance of 8%.
  Pension insurance with ABP. We take care of approximately 70% of the monthly contribution.
• 100% public transport reimbursement. Are you coming on foot, by bike or by car? You will then receive a reimbursement of € 0.18 per km (by car up to a max. of 40 km one way).
• Possibilities to develop yourself personally and professionally.
• The option to select additional employment benefits in exchange for gross salary, such as purchasing a bicycle and memberships.