**Job Description**
This PostDoc position at the Julius Center for Health Sciences and Primary Care, UMC Utrecht, is part of a ZonMw-funded project investigating long-term risks in post-COVID patients compared to individuals with similar post-viral complaints. The role involves working at the intersection of data science, epidemiology, and clinical research, specifically developing innovative methods to optimize the use of large-scale real-world data. The primary focus will be on developing and validating Natural Language Processing (NLP) models to extract clinically meaningful diagnoses, symptoms, signs, and disease durations related to infections and post-infection syndromes, including post-COVID, from extensive general practitioner data. The researcher will also explore advanced modeling techniques to improve model generalizability and robustness.
**Skills & Abilities**
• 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
• Results-oriented
• Enjoys working both independently and collaboratively in an interdisciplinary team
**Qualifications**
Required Degree(s) in:
• Computer science
• Computational linguistics
• AI
• Engineering
• Bioinformatics
• Comparable technical study
Other:
• Ph.D. in a relevant area (or dissertation pending defense)
**Experience**
Other:
• Experience in healthcare data research is an advantage.
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