PhD in AI for Multimodal Liver Disease & Pathology

KU Leuven; Vlaams-Brabant; On-site; EUR 17,000 - 23,000; Full time

Benefits offered by this job

State-of-the-art infrastructure

Multidisciplinary collaboration

PhD stipend per KU Leuven scholarships

Job summary

KU Leuven invites applications for a full-time PhD position to develop AI methods for multimodal analysis of chronic liver disease and liver cancer. Based in the Govaere Research Group, you will work with pathologists and clinicians to build models combining histopathology with molecular data and possibly MRI.

You will complete a doctoral program within four years, train in computational pathology, and contribute to manuscript writing and funding applications, joining a fast-moving,

Qualifications

• Master's degree in computer science, artificial intelligence, bioinformatics, computational biology, statistics or a closely related field.
• Strong programming skills, preferably Python; proficiency in R is an additional asset.
• Solid foundation in machine learning, deep learning, statistics or data science.

Responsibilities

• Complete a doctoral training programme and conduct original research leading to a PhD in AI and digital pathology for chronic liver disease and HCC.
• Develop, train and evaluate machine-learning and deep-learning models for whole-slide pathology and multimodal biomedical data.
• Collaborate with pathology, hepatology, oncology, radiology, molecular biology and biomedical AI researchers.

Skills

Python programming

R programming

Machine learning

Deep learning

Statistics / data science

Independent work

Education

Master's degree in CS/AI/Bioinformatics

Tools

Python

R

Job description

KU Leuven invites applications for a full-time PhD position to develop AI methods for multimodal analysis of chronic liver disease and liver cancer. Based in the Govaere Research Group, you will work with pathologists and clinicians to build models combining histopathology with molecular data and possibly MRI.

You will complete a doctoral program within four years, train in computational pathology, and contribute to manuscript writing and funding applications, joining a fast-moving,