Job Reference:
369d07e3e5a8
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A Fully Funded PhD in Machine Learning and Large Language Models (LLMs), Lausanne
About the Position:
The Lausanne University Hospital (CHUV) is one of five Swiss university hospitals. Through its collaboration with the Faculty of Biology and Medicine of the University of Lausanne and the EPFL, CHUV plays a leading role in the areas of medical care, medical research, and training.
Dr. Nazanin Sédille and Professor Oliver Y. Chén's teams develop new machine-learning and statistical methods and study large-scale data in health and disease. Their focus is threefold: (a) building new, methodologically exciting models to address real-world problems; (b) using these methods to (i) study the interplays between large-scale multimodal, multivariate, high-dimensional features, and when/how they may be associated with diseases cross-sectionally and longitudinally, and (ii) identify markers that support patient diagnosis and prognosis; (c) translating our algorithms into clinical decision support and patient health management apps.
Research Projects:
1. Better Biomarkers for Cardiovascular and Metabolomic Diseases: We aim to design large language models (LLMs) to discover biomarkers for cardiovascular and metabolomic diseases using insights from both machine intelligence and biology. Using these new methodological frameworks, we aim to identify cardiovascular biomarkers related to heart disease risk factors and clinical outcomes such as disease onset or progression. In parallel, we aim to identify diabetic biomarkers related to renal insufficiency and clinical outcomes such as diabetic onset or progression. Finally, we aim to quantify the disease pathways from risk factors to clinical outcomes via the discovered biomarkers.
2. Disease Prediction using Multimodal Data: We will design LLMs to identify, from multivariate, multimodal, potentially high-dimensional biomarkers, that can together improve the overall disease prediction accuracy as well as clinical explanation of the biomarkers.
3. Longitudinal Data Analysis and Early Disease Prediction: We aim to develop new methods that can unveil the longitudinal trajectories of the disease profile, forecast future disease progression, and inform targeted and more timely disease management, treatment, and prevention.
Your Profile:
* A master's degree and an undergraduate degree in disciplines relevant to (applied) mathematics, computer science, engineering, machine learning, or statistics
* An interest in developing new methods and applications and employing them to address real-world healthcare-related problems
* A team player
* The working language of the group is English. A good command of the French language is mandatory
* Strong programming skills related to machine learning, longitudinal methods, and large language models (LLMs)
* Experience in machine learning (LLMs), statistical modelling, and version control
We Offer:
1. Joint affiliations with the Lausanne University Hospital (CHUV) and the University of Lausanne
2. An interdisciplinary environment, and a supportive team. We strive for equality, diversity, and inclusion
3. Possibility to collaborate with international universities
4. Access to courses from the CHUV and the University of Lausanne
5. Possibility to access one of the furnished apartments offered in the surrounding neighborhoods in case of relocation in Switzerland
6. Discounts proposed on social and cultural events, thanks to the