Do you want to contribute to top quality medical research?

We are looking for an outstanding research specialist with keen interest in advanced statistical genetics, applied mathematics and machine learning that could drive the frontier of human genetics within the Endocrinology unit at the department of medicine, Huddinge.

Description of the subject area

At the Endocrinology unit we study the role of lipid metabolism in cardiometabolic diseases, as dyslipidemia, atherosclerosis, type 2 diabetes and MASLD/MASH, to improve the prevention, diagnosis, and treatment of these conditions. Molecular mechanisms of genetic variants, dietary, hormonal regulation, and lipoprotein metabolism are explored in human and preclinical models. Influence of diurnal rhythms, and novel drugs are studied, also in collaborations with industry. Members participate in national and international networks of associations and foundations, participate in multicenter clinical trials, and serve as experts in pathophysiology and pharmacology, molecular biology, biochemistry, genomics, cell-based and organoid systems, and mass spectrometry.

Your mission

You will contribute to a project on human genetics of Metabolic dysfunction–associated steatotic liver disease (MASLD), previously known as non-alcoholic fatty liver disease (NAFLD), which affects as many as a third of the population today. As with other complex diseases, MASLD has a strong genetic component. In this newly started project, you will develop computationally efficient statistical methods for rare variant association analysis of large-scale whole-genome sequencing data, with the aim of identifying potential new gene targets to treat the disease. Especially, you will focus on developing and optimizing methods to integrate qualitative and quantitative functional annotations with gene-/region-based methods to empower the detection of rare variants predisposing to MASLD. In addition, by applying deep learning methods, you will assess the capability of partitioned polygenic risk scores based on common and rare variants to identify disease subtypes.

This position demands expertise in handling and analyzing multidimensional large-scale sequencing data, and a deep understanding of existing methods, such as sequence kernel association and burden tests.

Eligibility requirements

To be eligible for employment as a Research Specialist, in addition to holding a Degree of Doctor, PhD, or having equivalent scientific expertise, the applicant must have demonstrated research expertise as well as have documented research experience after defending their doctoral dissertation.

In addition to the eligibility criteria, the applicant should demonstrate:

  • A strong background in mathematics and the mathematical modeling of complex systems, with advanced expertise in Python and C++ programming languages, and Unix/Linux environment. Additionally, the applicant must be at least familiar with R.
  • Experience with mainstream machine learning and statistical methodologies.
  • Experience with scientific code optimization and deployment for high-performance computing on CPU and GPU substrates.
  • Experience with analysis of and inference on complex networks.

Familiarity with the following topics:

  • Human genetics
  • Genome and exome-wide association study (GWAS, EWAS)
  • Analyses of enrichment of common and rare variants
  • Transcriptomic analysis
  • Mendelian randomization (MR) and meta-analysis
  • Biomedical statistics
  • Machine-/Deep-learning techniques 

Assessment criteria

It is particularly meritorious that the applicant has shown:

  • Proficient knowledge of mathematics and/or physics
  • Experience in handling large-scale whole-genome and whole-exome sequencing datasets, and a deep understanding of high-performance computation
  • Excellent communication skills in English, both in written and oral form, for the communication and dissemination of achieved results, and with collaborators
  • Several publications in relevant journals as first author

Moreover, teamwork capacity is very important for this job. Great emphasis will be placed on personal suitability.

After an overall assessment of the expertise and merits of the applicants in relation to the subject area, Karolinska Institutet will determine which of them has the best potential to contribute to a positive development of the activities at KI.

What do we offer?

A creative and inspiring environment with wide-ranging expertise and interests. Karolinska Institutet is one of the world's leading medical universities. Here, we conduct successful medical research and hold the largest range of medical education in Sweden. At KI, you get to meet researchers working with a wide range of specialisms and methods, giving you ample opportunity to exchange knowledge and experience with the various scientific fields within medicine and health. It is the crossover collaborations, which have pushed KI to where it is today, at the forefront of global research. Several of the people you meet in healthcare are educated at KI. A close relationship with the health care providers is important for creating groundbreaking top quality education and research. Karolinska Institutet is also a state university, which entitles you to several benefits through our collective agreement.



Endocrinology Unit

Department of Medicine, Huddinge

Choose to work at KI - Ten reasons why


We prefer that Your application is written in English, but You can also apply in Swedish. An application must contain the following documents: Resumé, qualifications and description of planned research, presented in accordance with Karolinska Institutet's qualifications portfolio.

Welcome to apply at the latest June 21, 2024.

The application must be submitted through the Varbi recruitment system.

Want to make a difference? Join us and contribute to better health for all

Type of employment Special fixed-term employment
Contract type Full time
First day of employment omg
Salary Månadslön
Number of positions 1
Full-time equivalent 100 %
City Flemingsberg
County Stockholms län
Country Sweden
Reference number STÖD 2-2430/2024
  • Stefano Romeo,
Union representative
  • Belinda Pannagel, SACO,
  • Sidinh Luc, SACO,
  • Mari Gilljam, OFR,
Published 10.Jun.2024
Last application date 21.Jun.2024 11:59 PM CEST

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