The Department of Medical Epidemiology and Biostatistics (MEB) is among the largest departments of epidemiology in Europe with special focus on increasing our knowledge of the aetiology of different diseases. Our department consists of researchers, doctoral students, biostatisticians, data collectors and database administrators as well as administrative personnel, in total some 250 staff. The department is situated at campus Solna. Further information can be found at

Do you want to contribute to top quality medical research?

To be a doctoral student means to devote oneself to a research project under supervision of experienced researchers and following an individual study plan. For a doctoral degree, the equivalent of four years of full-time doctoral education is required.

The research group

At Department of Medical Epidemiology and Biostatistics (MEB) of Karolinska Institutet (KI), we carry out epidemiologic research in a wide range of medical areas, including cancer, psychiatry, neurological diseases, etc. Our projects aim to increase knowledge about causes of diseases and to translate the knowledge towards clinical application. Biostatistical analysis is of central importance in the interdisciplinary research conducted at MEB. Much of our methodological tools relies on statistical genetics, molecular epidemiology as well as biostatistics. MEB has the largest critical mass of academic biostatisticians in Sweden and is one of the largest among Nordic countries. Overall, we provide a stimulating and active research environment that facilitates both internal and external collaborations with world-class scientists.

This project is under supervision of an interdisciplinary team, including Dr. Trung Nghia Vu experienced in developments and applications of statistical and computational methods for cancer large-scale omics data, Prof. Fang Fang with expertise in epidemiological studies such as the areas of psychological and neurological disease, Associate Prof. Mattias Rantalainen who has substantial expertise in statistical and
machine learning methodologies for predictive modeling in biomedical applications, and Prof. Yudi Pawitan with strong expertise in biostatistics, bioinformatics and high-throughput molecular data modeling. The supervisory team is highly experienced in the relevant subject areas and active in national and international collaborations.

The doctoral student project and the duties of the doctoral student

The advent of high-throughput technologies produces an avalanche of omics data and has revolutionised medical research. Omics data have been utilised to study biological mechanisms of diseases as well as to predict drug response of tumours toward precision medicine. This project will focus on the development of methodologies for analysing omics data and predicting drug responses from complex diseases including acute myeloid leukemia (AML) and Amyotrophic Lateral Sclerosis (ALS). The successful
candidate will analyse next-generation-sequencing (NGS) samples from different omics- data to discover biological features, then develop statistical and computational models to predict drug responses in both monotherapy and drug-combination settings.

For more information please contact Dr. Trung Nghia Vu, see email address below.

What do we offer?

A creative and inspiring environment full of expertise and curiosity. Karolinska Institutet is one of the world's leading medical universities. Our vision is to pursue the development of knowledge about life and to promote a better health for all. At Karolinska Institutet, we conduct successful medical research and hold the largest range of medical education in Sweden. As a doctoral student you are offered an individual research project, a well-educated supervisor, a vast range of elective courses and the opportunity to work in a leading research group. Karolinska Institutet collaborates with prominent universities from all around the world, which ensures opportunities for international exchanges. You will be employed on a doctoral studentship which means that you receive a contractual salary. Employees also have access to our modern gym for free and receive reimbursements for medical care.

Eligibility requirements for doctoral education

In order to participate in the selection for a doctoral position, you must meet the following general (A) and specific (B) eligibility requirements at latest by the application deadline.

It is your responsibility to certify eligibility by following the instructions on the web page Entry requirements (eligibility) for doctoral education.

A) General eligibility requirement
You meet the general eligibility requirement for doctoral/third-cycle/PhD education if you:

  1. have been awarded a second-cycle/advanced/master qualification (i.e. master degree) or
  2. have satisfied the requirements for courses comprising at least 240 credits of which at least 60 credits were awarded in the advanced/second-cycle/master level, or
  3. have acquired substantially equivalent knowledge in some other way in Sweden or abroad.*

Follow the instructions on the web page Entry requirements (eligibility) for doctoral education.

*If you claim equivalent knowledge, follow the instructions on the web page Assessing equivalent knowledge for general eligibility for doctoral education.

B) Specific eligibility requirement

You meet the specific eligibility requirement for doctoral/third-cycle/PhD education if you:

- Show proficiency in English equivalent to the course English B/English 6 at Swedish upper secondary school.

Follow the instructions on the web page English language requirements for doctoral education.

Verification of your documents
Karolinska Institutet checks the authenticity of your documents. Karolinska Institutet reserves the right to revoke admission if supporting documents are discovered to be fraudulent. Submission of false documents is a violation of Swedish law and is considered grounds for legal action.

Skills and personal qualities

- MSc in bioinformatics, computer science or information technology or related fields.

- Background in machine learning and bioinformatics

- Experience with analysis of next-generation sequencing data, especially establishing bioinformatics analysis pipeline for RNA-sequencing data and down-stream analysis of the gene-expression data.

- Experience in analyses of non-coding RNAs is an advantage.

- Experience with modeling omics data in medical applications is an advantage.

- Experience with employing high performance computers and parallel processing.

- Strong skills in programming using both R and C/C++.

- Personal characteristics:  Well-informed and curious concerning issues of health, biology and statistical problems; thoroughness in dealing with research data; interest and persistence in learning new tasks; ability to collaborate in a multidisciplinary group

Terms and conditions

The doctoral student will be employed on a doctoral studentship maximum 4 years full-time.

Application process

Submit your application and supporting documents through the Varbi recruitment system. Use the button in the top right corner and follow the instructions.

Your application should contain the following documents:

- A personal letter and a curriculum vitae (Swedish or English)
- Degree projects and previous publications, if any (Swedish or English)
- Any other documentation showing the desirable skills and personal qualities described above (Swedish or English)
- Documents certifying your general eligibility (see A above)
- Documents certifying your specific eligibility (see B above)


A selection will be made among eligible applicants on the basis of the ability to benefit from doctoral education. The qualifications of the applicants will be evaluated on an overall basis.

Karolinska Institutet uses the following bases of assessment:

- Documented subject knowledge of relevance to the area of research
- Analytical skill
- Other documented knowledge or experience that may be relevant to doctoral studies in the subject.

 All applicants will be informed when the recruitment is completed.

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

Type of employment Temporary position longer than 6 months
Contract type Full time
Reference number 2-2839/2020
  • Trung Nghia Vu,
  • Sofia Anderberg,
Union representative
  • Henry Wölling, SEKO,
  • Ann Almqvist, SACO,
  • Gunnel Brolin, OFR,
Published 20.Jul.2020
Last application date 10.Aug.2020 11:59 PM CET

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