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Computational PhD Stipend in Integrative Multi-omics in Metabolic Dysfunction–associated Steatotic Liver Disease

Syddansk Universitet (SDU)



Application deadline: 2 January 2025 at 23:59 hours local Danish time
The Center for Functional Genomics and Tissue Plasticity (ATLAS) at the Functional Genomics & Metabolism Research Unit, Department of Biochemistry and Molecular Biology, University of Southern Denmark, invites applications from outstanding candidates who are interested in joining our team as a PhD fellow. We have one position available from March 1, 2025, or as soon as possible thereafter. Application deadline: 2 January 2025 at 23:59 hours local Danish time

ATLAS
The overall aim of Center for Functional Genomics and Tissue Plasticity (ATLAS) is to obtain systems-level, mechanistic and cell type-resolved understanding of adipose and hepatic tissue plasticity in response to diet-induced obesity and regression. We apply a combination of functional genomics approaches, including single cell-sequencing, proteomics, in vivo targeting, and computational biology to obtain in depth mechanistic understanding of the plasticity of these tissues in mouse models as well as in humans undergoing weight-reducing surgery. ATLAS is supported by the Danish National Research Foundation.

The PhD stipend
We offer one PhD stipend in the center within the project described below. The PhD fellow will become part of the MadLab research group led by Assoc. Professor Jesper G. S. Madsen, and at the same time part of our highly ambitious and interdisciplinary research environment in ATLAS, particularly Work Package 4 on “Disease trajectories and biomarkers”, as well as the Functional Genomics and Metabolism Research Unit.

Multimodal Predictive Models for Metabolic Liver Disease
In this project, we aim to shed new light on the etiology of metabolic dysfunction–associated steatotic liver disease (MASLD). We are particularly interested in developing predictive algorithms for diagnosis and prognosis of MASLD. To develop such algorithms, we analyze a wide range of data modalities, ranging from clinical parameters to functional genomics readouts.

As a PhD student on this project, you will work in close collaboration with other PhD students and postdocs in MadLab and ATLAS to collect, curate, integrate, and analyze large-scale proteomics, as well as bulk and single-cell RNA-sequencing datasets derived from human liver, adipose tissue, and blood. To that end, you will build, train, and evaluate deep learning-based approaches, such as variational autoencoders.

For this project, hands-on experience with applied bioinformatics, and statistical programming (R or Python) is required, and experience with applied machine learning and/or liver, adipose tissue biology is considered an advantage.

We offer:

  • One three-year PhD position in a highly stimulating, supportive, international, and interdisciplinary research environment
  • Enrollment in the PhD school at the Faculty of Science and in the Research training programme in Bioinformatics, which allows the candidate to tailor a flexible individualized course program
  • Training in a wide range of skills including research management, communication, networking, presentations, writing of manuscripts etc.
  • Mentoring and career development
  • Research exchange to collaborating institution, depending on the interest of the PhD student
  • Access to state-of-the-art equipment, facilities and infrastructure
  • Opportunity to interact with an extensive network of national and international collaborators
  • A competitive salary and social benefits (e.g. health coverage, parental leave, social security etc.)
  • Dedicated assistance and support with various practical, social, and legal aspects (housing, visa, administration, tax etc.), especially for international candidates through our international staff office (ISO) and department

The research environment
ATLAS and MadLab are based in the Functional Genomics & Metabolism Research Unit, Department of Biochemistry and Molecular Biology, University of Southern Denmark. The research unit constitutes an international, ambitious, highly dynamic, and well-equipped working environment. The unit and the department have state-of-the-art facilities for next generation sequencing, single-cell transcriptomics, flow cytometry, mass spectrometry, metabolomics, bioimaging and transgenic mouse work. Strategic research alliances exist with Odense University Hospital (OUH).

Qualifications/requirements
We are looking for a highly motivated, dedicated, and ambitious candidate with:

  • A Master’s degree in Applied Mathematics, Data Science, Bioinformatics, Computational Biology, Biomedicine, Molecular biology, or a closely related field.
  • Strong communication and collaborative skills and an interest in working in an interdisciplinary environment
  • Documented experience with statistical programming (e.g., R or Python).
  • Documented experience with (single-cell) -omics data analysis.
  • Experience with applied machine learning, as well as adipose tissue and liver biology is considered an advantage.
  • Proficiency in spoken and written English.

For further information please contact Associate Professor Jesper Madsen ([email protected]).

Application, salary etc.
Appointment as a PhD Research Fellow is for three years. Employment stops automatically at the end of the period. The holder of the scholarship is not allowed to have other paid employment during the three-year period.

The successful applicant will be employed in accordance with the agreement on salaried PhD scholars between the Ministry of Finance and AC (the Danish Confederation of Professional Associations). Please check links for more information on salary (only available in Danish) and taxation.

The successful candidate will be enrolled at this university in accordance with faculty regulations and the Danish Ministerial Order on the PhD Programme at the Universities (PhD order).

Further information about the PhD-study can be found at the homepage of the University.

The University wishes our staff to reflect the diversity of society and thus welcomes applications from all qualified candidates regardless of personal background.

Application must be in English and made in the form of a Declaration of Interest including the following:

  • A letter stating your specific interest, motivation, and qualifications for the project in question (max. two pages) .
  • Detailed CV, including personal contact information.
  • Copies of diplomas, Bachelor as well as Master’s degree, including transcript of notes/grades.
  • At least two signed reference letters. Should your referees wish to send their letters directly to us, please have them use e-mail: [email protected] mentioning your name and the title of the position in the subject line. And please note that these also need to reach us before deadline.

Shortlisting may be used in the assessment process.
Incomplete applications and applications received after the deadline will neither be considered nor evaluated. This also applies to reference letters.

Applications will be assessed by an expert assessor/committee. Applicants will be informed of their assessment by the university.

Applications should be sent electronically via the link "Apply now". The faculty expects applicants to read the information "How to apply" before applying. Please note that the application documents should be in pdf-format and attached as three documents: motivation letter, CV and the remaining documents.

We recommend that as an international applicant you take the time to visit Work in Denmark where you will find information and facts about moving to, working and living in Denmark, as well as the International Staff Office at SDU.

Placering: Odense, Denmark

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Syddansk Universitet (SDU)

Campusvej 55, 5230 Odense M

SDU åbnede dørene for de første studerende i Odense i september 1966, og siden da er det gået stærkt. Vi har nu fem fakulteter med omkring 30.000 studerende, heraf mere end 15 % fra udlandet, og knap 4.000 ansatte fordelt på hovedcampus i Odense samt regionale campusser i Slagelse, Kolding, Esbjerg og Sønderborg og København.

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