PhD in Causal Machine Learning for Real World Evidence data

University of Copenhagen; København; On-site; DKK 320,000 - 420,000; Full time

Job summary

The University of Copenhagen invites applications for a highly motivated PhD fellow to join the Rasmussen Lab at the Novo Nordisk Foundation Center for Basic Metabolic Research (CBMR). The position starts on 1 January 2027 or after agreement and runs for 3 years as a PhD fellowship.

The project focuses on developing causal AI-based methods to understand and predict cardiometabolic disease using large-scale health data, with collaboration to international partners and enrolment as a PhD student

Qualifications

• Master's degree in Biology, Bioinformatics, Data Science or related sciences.
• The grade point average achieved is required.
• Professional qualifications relevant to the PhD project are desirable.
• Previous publications are advantageous.
• Relevant work experience or activities strengthen the application.
• A curious mindset with interest in applying AI to health data.
• Excellent English communication skills, both written and spoken.

Skills

English proficiency

Curious mindset

Publications experience

AI health data interest

Education

Master's degree in Biology / Bioinformatics / Data Science

Job description

The University of Copenhagen is seeking a highly motivated and talented PhD fellow to commence January 1, 2027, or after agreement in the Rasmussen Group at the Novo Nordisk Foundation Center for Basic Metabolic Research (CBMR), University of Copenhagen.

About Us

The Novo Nordisk Foundation Center for Basic Metabolic Research (CBMR) is an academic research Center that pioneers 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. The Center's uniquely multi- and interdisciplinary approach combines research in genetics, physiology and pharmacology, to better understand the complex interplay of the many factors that drive cardiometabolic disease. You can learn more in the Executive Summary of CBMR's Strategy 2024-2028.

CBMR was established in 2010 at the Faculty of Health & Medical Sciences and has been located in the Maersk Tower at Panum since 2017. The around 260 employees create an international, highly collaborative research environment across disciplines.

Our Research

The Rasmussen Lab develops and applies advanced AI and bioinformatics methods to understand cardiometabolic disease and advance precision health. A central focus is the creation of AI-driven medical digital twins by integrating large-scale genomics, multi-omics, and longitudinal health data. We are an interdisciplinary and collaborative team spanning machine learning, computational biology, and clinical research, working closely with leading international academic partners. The group provides a supportive, inclusive, and international environment, where we value diversity across backgrounds and career stages and foster a culture of teamwork, open science, and mutual support.

Project Description

The PhD project focuses on developing causal AI-based methods to better understand and predict cardiometabolic disease using large-scale health and biological data. The work will contribute to building medical digital twins: computational representations of individuals that capture health trajectories over time. By combining diverse data sources and modern machine learning methods, the project aims to improve how we model disease risk, progression, and treatment response. The research sits at the intersection of data science, biology, and medicine, and involves close collaboration with clinical and international partners. The position offers a unique opportunity to work with world-leading datasets and contribute to the development of next-generation precision health approaches.

Principal supervisor:

Professor, Simon Rasmussen
[e-mail]

Start:

January 1, 2027

Duration:

3 years as PhD fellow.

Profile

Required qualifications:

• Master's degree in Biology, Bioinformatics, Data Science or related sciences. Please note that your master's degree must be equivalent to a Danish master's degree (two years).
• The grade point average achieved
• Professional qualifications relevant to the PhD project
• Previous publications
• Relevant work experience
• Other professional activities
• A curious mindset with a strong interest in application of AI to health data
• Excellent English communication skills, both written and oral

Terms of Employment

The employment consists of 3 years as PhD fellow. The starting date is January 1, 2027, or after agreement.

The employment as PhD fellow is conditioned upon the applicant's successful enrolment as a PhD student at the Graduate School at the Faculty of Health and Medical Sciences, University of Copenhagen. This requires submission and acceptance of an application for the specific project formulated by the applicant. The PhD study must be completed in accordance with The Ministerial Order on the PhD programme (2013) and the Faculty's rules on achieving the degree.

Salary, pension and terms of employment are in accordance with the agreement between the Ministry of Taxation and The Danish Confederation of Professional Associations on Academics in the State.

Questions

For further information about the position, please contact Professor, Simon Rasmussen at [e-mail]. For questions regarding the recruitment procedure, please contact HR at [e-mail].

General information about PhD studies at the Faculty of Health and Medical Sciences is available at the Graduate School's website.

The University of Copenhagen International Staff Mobility office offers support and assistance to all international researchers on all issues related to moving to and settling in Denmark.

The Further Process

After the expiry of the deadline for applications, the authorized recruitment manager selects applicants for assessment on the advice of the hiring committee. All applicants are then immediately notified whether their application has been passed for assessment by an unbiased assessor. Once the assessment work has been completed, each applicant has the opportunity to comment on the part of the assessment that relates to the applicant him/herself.

You can read about the recruitment process at www.employment.ku.dk/faculty/recruitment-process.

The applicant will be assessed according to Ministerial Order No. 242 of March 13, 2012, on the Appointment of Academic Staff at Universities.

The University of Copenhagen wishes to reflect the diversity of society and welcomes applications from all qualified candidates regardless of their personal backgrounds.