Affiliation: University of Manchester

Keywords: medical image computing, machine learning / artificial intelligence, health data science, musculoskeletal disorders, osteoarthritis, research translation


Orcid identifier

dr. Claudia Lindner

Dr Claudia Lindner is a certified IT Specialist in Software Engineering (2002, German Chamber of Commerce and Industry). She received the BSc (2005) and the MSc (2007) degrees in Computer Science, both with distinction, from the Heinrich Heine University Düsseldorf, Germany, and the PhD (2014) degree in Medical Image Computing from the University of Manchester, UK. She joined the University of Manchester as a Research Associate in 2014 and was promoted to Research Fellow in 2016. Claudia held a Rutherford Fund Fellowship at HDR UK from 2017 to 2021. Currently, she is a Sir Henry Dale Research Fellow jointly funded by the Wellcome Trust and the Royal Society.

Claudia’s career includes over 15 years in the development and application of computational methods working within multi-disciplinary teams in industrial and academic settings in Germany, Australia and the UK. She is the Early Career Researcher Lead for the Christabel Pankhurst Institute for Health Technology Research and Innovation, and a member of the steering committee of the World COACH Consortium, an international collaboration of experts studying osteoarthritis and morphological data of the hip. Her research was awarded multiple competitive grants by UK Research and Innovation, the Wellcome Trust, Versus Arthritis and the UK National Institute for Health Research. Claudia has won several national and international awards. She was Highly Commended at the 2019 L’Oréal-UNESCO UK & Ireland Fellowships for Women in Science programme, and received the Wellcome-Beit Prize for outstanding biomedical researchers in 2021.

Claudia’s research interests include the automated analysis of medical images to study, diagnose and manage musculoskeletal disorders. She uses methods from computer vision, machine learning and data science to develop accurate systems for outlining and analysing structures in widely used medical images such as radiographs. To enable patient benefit from digital healthcare research, she develops general guidance and strategies on how to bring such systems into the clinic. The overall goal of Claudia’s work is to transform clinically collected image data into useful medical information to benefit healthcare at individual and societal levels – driven by her passion to make a difference to people’s lives.