Dr. Ulrike Dydak

Professor

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Biography

Ulrike Dydak is a Professor in the School of Health Sciences at Purdue University and serves as the Director of the Purdue Life Science MRI Facility. She completed her Master’s degree in physics at the University of Vienna, Austria, and earned her PhD from the Swiss Federal Institute of Technology (ETH Zürich). Her research focuses on the development and application of novel magnetic resonance imaging (MRI) spectroscopy (MRS) techniques for clinical life sciences studies, particularly in relation to metal-induced parkinsonism and neurological disorders. Dydak’s work includes investigating manganese-induced neurotoxicity among welders by employing MRS techniques to assess changes in neurotransmitters such as GABA and Glutamate, as well as evaluating metal deposition in the human brain through quantitative MRI. She has collaborated on projects addressing postpartum depression and addiction using MRI, and her findings contribute to understanding the connection between neurotoxicity and mental health issues.

Research Interests

Experience

Professor

— Present

Purdue University • West Lafayette, IN

Educational and research duties in the School of Health Sciences, focusing on MRI facility management and neuroimaging research.

Awards

#2018

Outstanding Graduate Mentor Award

#2018

Robert R. Landolt Excellence in Teaching Award

#2017

Midcareer Research Award

#2015

Purdue University Faculty Scholar

#2011

Outstanding New Environmental Scientist Award

Courses

HSCI 312 - Radiation Science Fundamentals HSCI 672 - MRI Quality Assurance HSCI 590 - Magnetic Resonance Spectroscopy

Requirements for Purdue University

Master Program
Requirements
GPA Requirement
Required:3.5
TOEFL
Listening
Required:22
Reading
Required:22
Writing
Required:22
Speaking
Required:22
Total
Required:100
IELTS
Listening
Required:7
Reading
Required:7
Writing
Required:7
Speaking
Required:7
Overall
Required:7.5
Duolingo
Overall Score
Required:135
Overall
Required:135
Prerequisites
Bachelor's degree in CS or related field Foundational concepts of computer science Data structures Computer architecture Operating systems Mathematics through differential equations Linear and matrix algebra
Application Checklist
  • Official Transcripts
  • Academic Statement of Purpose
  • Personal History Statement
  • Resume
  • Three Letters of Recommendation
  • CS Supplementary Form
Specialization Notes

GRE is not required.