Postdoctoral Researcher in Biostatistics, with focus on prostate cancer

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



Division
Prostate cancer is the most common cancer and a leading cause of cancer death among men in the Western world.

In Sweden, over 10,000 men are diagnosed with prostate cancer and 2,500 die of the disease every year. There are substantial levels of inefficient opportunistic PSA screening in Sweden.

The overarching aim of our research is to develop a personalized prostate cancer diagnostic pipeline using a combination of genomics, proteomics and imaging, which will have better sensitivity to detect high-risk prostate cancer and at the same time decrease the harms associated with current PSA screening. Reliable risk prediction in every step of this pipeline is key for advancing both prevention and diagnostics of prostate cancer.

This research is anchored in the STHLM3 study, in which we prospectively evaluated S3M – a prediction algorithm using 6 plasma protein markers, 250 genetic markers and clinical variables – in 58,143 men during 2012-2014 as a screening tool for prostate cancer. For more information about the STHLM3 study, see PubMed ID 26563502.

The research is highly trans-disciplinary with collaborations within Sweden and internationally. Multiple world-class clinical trials and data collection efforts have been based at MEB and new efforts are in progress, e.g. the ongoing STHLM3-MRI trial to assess the role of MRI to improve prostate cancer diagnostics.

Description of the work

The main responsibilities are to perform research and be involved in supervision of PhD students. The work tasks involve the development and application of statistical/machine learning methodology for prediction and prediction regions, as well as design and methodology development for clinical trials and observational register-based studies. The position involves responsibility for maintaining a high level of statistical/mathematical competence, and to absorb necessary knowledge on cancer aetiology and epidemiology and register based research.


Entry requirements and qualifications
A person is eligible for a position as Postdoctoral Researcher if he or she has obtained a PhD no more than seven years before the last date of employment as postdoc.

The position requires a university degree in mathematics/statistics and a PhD degree with focus on machine learning, statistics, biostatistics, or a closely related field. The ideal applicant should be experienced in methodology development and have a strong interest in applications. Experience in the design and analysis of clinical trials or epidemiological studies, from working with register-based data, and interpretational skills for presenting results in scientific journals 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.

Proven skills in programming, 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 specific 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:

- 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
- A complete list of publications
- A summary of current work (no more than one page)
- Verifications for crediting of illness, military service, work for labour unions or student organisations, parental leave or similar circumstances
- Verification from the thesis defence committee or the equivalent (only if the thesis defence is scheduled within three months after the application deadline)
The application is to be submitted through the MyNetwork recruitment system.

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