Your Twin learns with you

30% off annual Pro20% off monthly Pro

Ends in00h00m00s

Publisher
source

University of Copenhagen

Postdoctoral Fellowship in Wearable Data Science, Multi-Omics Integration, and Machine Learning for Precision Cardiovascular Health University of Copenhagen in Denmark

Degree Level

Postdoc

Field of study

Computer Science

Funding

This is a full-time, fixed-term postdoctoral position for two years. Salary, pension, and employment terms follow the agreement between the Danish Ministry of Finance and the AC (Danish Confederation of Professional Associations); a supplement may be negotiated depending on qualifications. Eligible applicants may receive tax reductions if they hold a PhD and have not lived in Denmark during the previous 10 years.

Deadline

Nov 29, 2026

Country flag

Country

Denmark

University

University of Copenhagen

Apply for this position

Keywords

Computer Science
Biostatistics
Deep Learning
Biology
Digital Health
Medical Science
Glucose Monitoring
Omics
Cardiometabolic Health
Statistics
Insulin
Bioinformatic
ML

Suggested positions

Publisher
source

Jordi Merino

University of Copenhagen

Country flag

Denmark

This postdoctoral fellowship is based at the Novo Nordisk Foundation Center for Basic Metabolic Research at the University of Copenhagen , where the successful candidate will join an interdisciplinary and highly collaborative environment focused on cardiometabolic health. The project sits at the intersection of wearable data science , multi-omics integration , and machine learning . It will use high-resolution continuous glucose monitoring and other digital health streams, together with genomics...

Computer Science
Biomedical Engineering
Biostatistics
+15 more

6 days ago

Publisher
source

KTH Royal Institute of Technology

Country flag

Sweden

KTH Royal Institute of Technology is offering a postdoctoral position in multi-omics machine learning and computational cancer biology within the A Lundberg Lab , which is part of the SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS) . The lab is based at SciLifeLab Stockholm and KTH and focuses on computational approaches for cancer precision medicine . The project centers on understanding the molecular mechanisms behind cancer aggressiveness, metastasis, and treatm...

Computer Science
Biomedical Engineering
Biostatistics
+11 more

1 week ago

Publisher
source

The University of Texas Rio Grande Valley

Country flag

United States

University of Texas Rio Grande Valley is advertising a Postdoctoral Fellow position in Human Genetics , with research focused on large family-based data sets , multiomics data analysis , and the incorporation of machine learning into multiomics workflows. The role includes developing, testing, and analyzing research projects; helping build a platform for integrating multiomics data; writing research summaries; assisting with progress reports; publishing peer-reviewed papers; and presenting findi...

Computer Science
Biology
Mathematics
+7 more

1 month ago

Publisher
source

University of Kentucky

Country flag

United States

The Emfinger Lab in the Barnstable Brown Diabetes Center at the University of Kentucky is recruiting a Postdoctoral Scholar in islet biology and machine learning . The lab studies factors that drive diabetes risk by altering insulin secretion and action, using omics data , computational approaches, and wet-lab validation in mice and human tissues. The postdoc will help collect data, analyze large datasets, prepare manuscripts, and present work at conferences. The environment is described as open...

Metabolism
Computer Science
Biostatistics
+7 more

1 month ago

Publisher
source

The Ohio State University

Country flag

United States

This postdoctoral scholar position is based in the Center for Biostatistics at The Ohio State University and is designed for specialized research training, education, and experience under the guidance of a center-affiliated scientific mentor. The role centers on developing and applying longitudinal, survival, and joint longitudinal-survival models to study disease progression, changing risk, and clinically relevant outcomes. The scholar will also build reproducible computational pipelines that i...

Computer Science
Epidemiology
Biomarker Research
+11 more

5 days ago

About this position

The University of Copenhagen is seeking a postdoctoral researcher for a project on wearable data science, multi-omics integration, and machine learning for precision cardiovascular health. The position is based at the Novo Nordisk Foundation Center for Basic Metabolic Research (CBMR), located in the Maersk Tower at the Panum Institute.

The successful candidate will join the Merino Group and collaborate with SMARTbiomed, an international partnership involving Aarhus University, the University of Oxford, and the University of Copenhagen. CBMR provides an interdisciplinary research environment spanning genetics, physiology, pharmacology, metabolism, and cardiometabolic health, with approximately 260 employees working across complementary research areas.

The project will develop new statistical and machine-learning methods for high-resolution continuous glucose monitoring data. Rather than relying only on standard summary measures, the research will examine distinct patterns of glucose elevation and use interpretable deep-learning models for long glucose sequences to identify subtypes within type 2 diabetes. These subtypes will be studied in relation to cardiometabolic risk, disease progression, treatment response, and complications.

The postdoctoral researcher will also integrate continuous glucose monitoring with digital health measurements such as physical activity, sleep, diet, and heart rate. These data will be combined with genomics and other omics layers to investigate individual susceptibility to dysglycaemia and discover disease markers and biological pathways. An important outcome will be open-source software that enables the wider research and clinical communities to use the developed methods.

The research will be conducted in a collaborative setting connecting quantitative methods, digital health, biomedical data science, and precision diabetes research, under the scientific environment of CBMR and its partner networks.

Funding details

This is a full-time, fixed-term postdoctoral position for two years. Salary, pension, and employment terms follow the agreement between the Danish Ministry of Finance and the AC (Danish Confederation of Professional Associations); a supplement may be negotiated depending on qualifications. Eligible applicants may receive tax reductions if they hold a PhD and have not lived in Denmark during the previous 10 years.

What's required

Applicants must hold a PhD in biostatistics, bioinformatics, computer science, data science, epidemiology, or a related quantitative field. They should have expertise in high-resolution time-series or longitudinal data, ideally from wearable devices such as continuous glucose monitors, accelerometers, or heart-rate sensors; strong machine-learning skills including deep learning for sequential data; experience with large datasets; proficiency in Python and/or R; and experience developing reproducible, open-source software. Experience integrating genomic or other omics data is advantageous. Applicants should demonstrate an active interest in diabetes, cardiovascular disease, and metabolism, a record of scientific productivity in peer-reviewed journals, strong communication and multidisciplinary teamwork skills, experience supervising researchers at different levels, and excellent written and spoken English. The application must include a motivated letter, CV, certified or signed PhD and MSc certificates, and a publication list.

How to apply

Submit an online application in English by clicking “Apply now” in the vacancy advert. Upload a one-page motivated letter, CV, certified or signed PhD and MSc certificates, and publication list, all in PDF format, by November 29, 2026 at 23:59 CET.

ApplyKite TwinLearns as you apply

Make your next move.

Prepare your application

Review drafts and confirm requirements with the university.