Postdoctoral Researcher in Cardiometabolic Disease Modeling
2 days ago
About Us
The University of Copenhagen's Novo Nordisk Foundation Center for Basic Metabolic Research (CBMR) is a pioneering academic research center dedicated to advancing groundbreaking research towards better cardiometabolic health.
Through collaborative interdisciplinary research from single-cell genomics to whole-body systems, CBMR aims to transform the basic understanding of cardiometabolic health and accelerate its translation into prevention and treatment strategies.
Our Research
The Rasmussen Lab focuses on developing and applying computational algorithms such as machine and deep learning for analysis and integration of multi-omic and multi-modal data within cardiometabolic disease. We develop supervised, unsupervised, self-supervised, and generative models to learn across multiple types of data rather than treating each data modality in isolation.
Job Description
The aim of the postdoc project is to develop patient-level multi-modal foundation models for studying cardiometabolic disease. Using data from large international biobanks, such as UKB, All of Us, and Project 10K, you will take part in developing and training state-of-the-art deep learning-based foundation models. This includes methodologies such as neural networks, variational autoencoders, transformers, and more.
Profile
The Postdoc fellowship is aimed at early-career researchers with a basic science background or clinicians who aspire to a career in academic medicine. We are particularly interested in candidates who are familiar with integrative research approaches within the broad area of basic cardiometabolic research with an application toward human pathophysiology.
- A PhD in Biology, Bioinformatics, Computational Biology, Computer Science, Data Science, or another relevant research field.
- An excellent scientific track record in relation to career stage.
- Prolonged knowledge of machine learning and/or deep learning.
- Knowledge of analysis of bulk or single-cell omics datasets.
- Experience in programming is strongly desirable.
- Excellent English communication skills, both written and oral.
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