Karolinska Institutet, MEB

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 ki.se/meb

Description of the work
There are few medical issues that have generated as much controversy as screening for breast cancer. For decades our biological and clinical understanding of breast cancer has been based on three therapeutically predictive biomarkers: estrogen (ER), progesterone (PR) receptors and the human epidermal growth factor receptor-2 (HER2). Today, we recognize that breast cancer biology is more complex; as well, clinical oncologists routinely use additional biomarkers and gene expression signatures (e.g. Ki-67/IHC4, MammaPrint or Oncotype-Dx) to recommend breast cancer treatments. Despite this deeper understanding of breast cancer biology and increasing clinical use of biology-driven breast cancer therapeutics, we lack population-based estimates of the extent that these ever more costly breast cancer subtype-targeted diagnostics and therapeutics actually reduce breast cancer mortality, improve quality of life, or otherwise prove cost-effective. The position will be focused on the application and development of microsimulation models to evaluate the population level effectiveness of breast cancer screening and treatment, based on merging trial data with population based register data. The work will be carried out in close collaboration with researchers at University of California San Francisco (UCSF) and at MD Anderson.

The postdoc candidate is also expected to supervise PhD students, absorb necessary knowledge on cancer aetiology and to maintain a high level of statistical/mathematical competence with focus on simulation modeling, clinical trials, epidemiology, and register based research.

Qualifications
The position requires a PhD degree with focus on machine learning, statistics, biostatistics, or a closely related field. The ideal applicant should be experienced in the development of microsimulation models and have a strong interest in disease modeling. Experience in health economic modeling and working with register-based data are strong merits. Further, experience from applications of statistics or machine learning methods in medicine and/or epidemiology are also considered strong merits, together with experience from cross-disciplinary research in a cancer research environment. Strong programming skills are a must and should include experience with at least one compiled language.

Proven skills in a statistical language, preferably in R, are required (additional experience from SAS or STATA is considered a plus). The applicant should also be able to manipulate complex datasets. Written and spoken fluency in English is essential.

Personal characteristics
The applicant should be highly collegial, and be able to work well in a cross-disciplinary team as well as having the ability to work independently. Further, the applicant should possess exceptional organizational skills, know how to successfully multitask, and should be able to describe past examples of having developed structured approaches to solving unanticipated and complex problems. Excellent oral and written communication skills in English are required, along with experience with writing and publishing research articles in English.

The applicant should have excellent analytical skills, possess curiosity and creativity, and have capacity to take responsibility for research projects. Further, the applicant should have the skill set to be involved in supervision of PhD students, including the necessary communication skills.

Application process
An employment application must contain the following documents in English or Swedish:

  1. A complete curriculum vitae, including date of the thesis defence, title of the thesis, previous academic positions, academic title, current position, academic distinctions, and committee work
  2. A complete list of publications
  3. A summary of current work (no more than one page)

The application is to be submitted through the Varbi recruitment system.

The position is for one year with the possibility of extension

Type of employment 临时职位(6个月以上)
Contract type Full time
Number of positions 1
Working hours 100%
City Stockholm
County Stockholms län
Country Sweden
Reference number 2-2381/2019
Contact
  • Martin Eklund, martin.eklund@ki.se
  • Lina Werner, lina.werner@ki.se
Union representative
  • Ann Almqvist, OFR, ann.almqvist@ki.se
  • Henry Wölling, SEKO, henry.wolling@ki.se
  • Ulrika Zagai, SACO, ulrika.zagai@ki.se
Published 06.May.2019
Last application date 16.May.2019 11:59 PM CET

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