Dr. Theresa Wimberley

Associate Professor

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Biography

Theresa Wimberley is a senior researcher at the National Centre for Register-based Research at Aarhus University. Her work focuses on investigating the causes and consequences of mental and neurological disorders, including schizophrenia, ADHD, and epilepsy. Wimberley utilizes register data, such as hospital and socio-economic databases, to provide insights into epidemiological research questions that can benefit the population, particularly vulnerable groups in society. She holds a master's degree in statistics obtained in 2009 and a PhD in medicine/public health awarded in 2016. Her research interests center on how treatments work and how diseases relate to various health challenges while examining the roles of genetics and environment in disease development. Wimberley is committed to finding ways to prevent diseases and improve treatment methods to enhance quality of life. She has extensive experience in applied biostatistics, epidemiology, pharmacoepidemiology, and register-based research, and she is responsible for managing key aspects of study design and data analysis. Wimberley teaches postgraduate courses in epidemiology and register-based research and supervises PhD students. Additionally, she serves as an ad-hoc peer reviewer for scientific research articles and actively participates in interdisciplinary international research collaborations as part of European Union consortia such as CRESTAR, PRIME, and TIMESPAN.

Research Interests

Requirements for Aarhus University

Master Program
Requirements
GPA Requirement
Required:3
IELTS
Overall
Required:6.5
TOEFL
Total
Required:83
Prerequisites
Bachelor's degree in a relevant field Specific credit requirements in programming, algorithms, and computer systems
Application Checklist
  • Official Bachelor's degree certificate
  • Official transcripts of records
  • Course descriptions
  • Curriculum Vitae (CV)
  • Documentation of English language proficiency
Specialization Notes

Department of Computer Science offers tracks in Software Efficiency, Cryptography, and Data Science.