Postdoc in Host-Microbiome Multi-omic Data Science

Freelio; Odense; On-site; DKK 420,000 - 520,000; Full time

Job summary

Arumugam Group at Odense University Hospital seeks a postdoc to advance deep learning methods for host–microbiome multi-omics data in liver disease projects. You will contribute to research, teaching, and guidance within multi-omics data science teams.

The role emphasizes developing novel ML approaches, collaborating across disciplines, and advancing graph-based models in a high-impact translational setting.

Qualifications

• PhD in computer science (informatics), mathematics, physics, bioinformatics, or biology with strong software development experience.
• Academic background with machine learning and statistical analysis.
• Strong programming skills and experience using deep learning frameworks (e.g., Python, NumPy, PyTorch, TensorFlow).
• Experience with deep learning model architectures including autoencoders and graph neural networks.
• Familiarity with explainable AI methods for model interpretation.
• Experience in HPC environments using UNIX and collaboration across teams.

Responsibilities

• Improve and expand current deep learning approaches and develop novel methods.
• Lead and participate in ongoing data science projects within consortia.
• Collaborate with clinicians, veterinarians, biologists, and bioinformaticians for proper interpretation of results.

Skills

Python

PyTorch

TensorFlow

Deep learning

Graph neural networks

XAI

UNIX

Teamwork

Education

PhD in computer science (informatics)

Tools

UNIX

Job description

Om stillingenA position as a postdoc (100% time) is vacant at theArumugam Group, Research unit of Medical Gastroenterology ,the Department of Clinical Research , Faculty of Health Sciences , University of Southern Denmark. The position is limited to 3 years with the possibility of extension.

Research tasks The position as a postdoc consists of research, teaching, professional development, and guidance inHost-Microbiome Multi-omic Data Science. We seek a data scientist to derive insights from host-microbiome multi-omics data in multiple consortium projects studying human and animal health, including GALAXY/MicrobLiver studying liver fibrosis ( https://www.sdu.dk/en/forskning/galaxy ), MICROB-PREDICT studying late-stage liver cirrhosis ( https://microb-predict.eu/ ), and PIG-PARADIGM to combat antimicrobial resistance (AMR) in pig production ( http://pig-paradigm.net ). We strive to integrate and interpret these data derived from microbiome (e.g., metagenomics, metatranscriptomics, viral metagenomics, metabolomics, metaproteomics) and host (e.g., genetics, proteomics, circulating metabolomics) in collaboration with international data science partners (e.g., EMBL-Heidelberg; University of California, Davis) and other project partners. The current state-of-the-art for multi-omics integration and interpretation leaves much to be desired. Fortunately, our ongoing work leveraging a deep learning approach (autoencoders) integrates multi-omics data and generates biologically relevant insights using a biologically informed machine learning framework. Our ambition is to strengthen and expand this research direction into graph-based approaches such as graph neural networks.

In this position, you will be:

• Responsible for improving and expanding our current deep learning approaches, while also having a chance to create your own novel approaches.
• Expected to participate in and lead existing data science projects within these consortia and the Arumugam group; and are highly encouraged to initiate new cutting-edge research projects.
• Expected to interact and collaborate with other clinical researchers, veterinarians, biologists, and bioinformaticians in these consortia to enhance and ensure proper interpretation of experimental results.

Expectations of qualifications The applicant who is hired must have a Ph.D. degree and documented research experience in one or more of the areas/fields mentioned below, with strong experience in software development.

• Computer science (informatics)
• Mathematics
• Physics
• Bioinformatics
• Biology

Required qualifications:

• PhD in computer science (informatics), mathematics, physics, bioinformatics, or biology with strong experience in software development.
• Academic preparation as well as experience in machine learning and statistical analysis.
• Strong programming skills and experience using deep learning frameworks (e.g., Python, NumPy, PyTorch, TensorFlow).
• Experience with deep learning model architectures, including autoencoders, graph neural networks, and related neural network models.
• Familiarity with explainable AI (xAI) methods for interpreting machine learning and deep learning models.
• Experience in a high-performance computing environment using any flavor of UNIX.
• Demonstrated capacity for effective teamwork.
• Proven track record showing scientific productivity in peer-reviewed journals.
• Excellent English communication skills, both written and oral.

Preferred qualifications:

• Experience in applying deep learning to biological problems.
• Basic understanding of human disease biology and/or microbiology.
• Experience in analyzing metagenomic datasets from host-associated microbiota.
• Experience in handling multi-omics data, including metabolomics and proteomics.
• Experience in distributed and cloud computing technologies.
• Experience in supervising other researchers at different levels.
• International mobility.

The Postdoc fellowship is aimed at early-career researchers with a background in basic science. We are particularly interested in candidates with strong analytical skills and interdisciplinary experience. Candidates with a solid data science background but lacking biological training are strongly encouraged to apply and include a statement about their motivation for this position and how they anticipate addressing this.

Research strategy for OUH and the Department of Clinical Research

The joint research strategy for the Department of Clinical Research and Odense University Hospital sets the direction for our shared research efforts in the years ahead. Rooted in the vision –We conduct research together to shape the patient care of the future – it focuses in particular on: cross-disciplinary research – with people at the centre; strong research environments – as drivers of development; and the research journey – from idea to impact. Further information on the joint research strategy of the Department of Clinical Research and Odense University Hospital is available here.

Further information

For further information, please contact Group Leader Mani Arumugam, Department of Clinical Research, e-mail: [email], phone: + [telefon] or Head of Department at the Department of Clinical Research Rikke Leth-Larsen, e-mail: [email], phone: [telefon].

Application deadline

September 09, 2026, at 23.59 hrs. (CET/CEST).

Salary and terms of employment

The applicant will be employed in accordance with the agreement between the Ministry of Finance and AC (the Danish Confederation of Professional Associations). The position as Postdoc is placed within salary steps 4–8 of the Danish state salary scale, depending on seniority. In addition, a centrally agreed postdoc allowance is paid, and further qualification- and function-related allowances may be negotiated. The work location will be at Campusvej 55, 5230 Odense M.

Assessment

Shortlisting will be used as part of the initial selection process. Assessment of shortlisted applications will be done under the existing Appointment Order for universities. Shortlisted applications will be assessed by an assessment committee. The committee may request additional information, and, if so, it is the responsibility of the applicant to provide the necessary material. When the assessment committee has submitted its report, the applicants will receive part of the evaluation that concerns themselves. References will be obtained for the preferred candidate from their current and previous employers. Applicants invited for interview should expect to complete a work-related personality assessment.

Living and working in Denmark

Foreign applicants will be offered Danish language training as part of the employment. The International Staff Office (ISO) at SDU provides a variety of services for new employees, guests and people who consider applying for a job at the University of Southern Denmark. The University wishes our staff to reflect the diversity of society and thus welcomes applications from all qualified candidates regardless of personal background.