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The Department of Medical Epidemiology and Biostatistics conducts research in epidemiology and biostatistics across a broad range of areas within biomedical science. The department is among the largest of its type in Europe and has especially strong research profiles in psychiatric, cancer, reproductive, pediatric, pharmaco, genetic, and geriatric epidemiology, eating disorders, precision medicine, and biostatistics.
Part of the success of our department is due to our collaborative spirit where one factor is that researchers at the Department share and co-finance common resources (e.g., IT and an applied biostatistics group). The department is situated at campus Solna. Further information can be found at http://ki.se/en/meb
With 1.1 million new diagnoses every year, prostate cancer (PCa) is the most common cancer in men in developed countries. The biopsy Gleason grading system is the most important prognostic marker for prostate cancer but suffers from significant inter-observer variability, limiting its usefulness for individual patients. The Gleason grade is determined by pathologists on hematoxylin and eosin (H&E) stained tissue specimens based on the architectural growth patterns of the tumor.
Automated deep learning systems have shown promise in accurately grading prostate cancer. Several studies have shown that these systems can achieve pathologist-level performance. Our research group has recently demonstrated that using convolutional neural networks, it is possible to obtain results on par with experienced human pathologists. We are now looking for a research assistant with knowledge in image analysis, digital pathology, and deep learning to continue this work.
The candidate is also expected to supervise PhD students, absorb necessary knowledge on cancer aetiology and to maintain a high level of statistical and machine learning competence with focus on image analysis using AI-methods like convolutional neural networks.
The ideal applicant should be experienced in image analysis, the development of deep learning models and have a strong interest in prostate pathology. Experience from different digital pathology platforms, in particular Philips Ultrafast Scanner, is essential. 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 have to include experience from Python and preferably also Tensorflow or PyTorch and Matlab. A PhD degree (or the equivalent) with focus on image analysis, machine learning, statistics, biostatistics, or a closely related field is a merit.
The applicant should also be able to manipulate complex datasets, in particular wholeslide images (WSIs), and have experience from creating and managing databases for such images. Written and spoken fluency in English is essential. Knowledge of Swedish and other Nordic languages is a merit, as the position will involve reading of pathology reports and clinical notes, as well as communication with health care staff.
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.
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. Karolinska Institutet is a state university, which entitles to several benefits such as extended holiday and generous occupational pension. Employees also have access to our modern gym for free and receive reimbursements for medical care.
Location: Solna
Welcome to apply at the latest 31 december 2019
The application is to be submitted through the Varbi recruitment system.
Permanent position are initiated by a six months trial period.
Type of employment | Special fixed-term employment |
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Contract type | Full time |
First day of employment | According to agreement |
Salary | Monthly salary |
Reference number | 2-6285/2019 |
Contact |
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Union representative |
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Published | 10.Dec.2019 |
Last application date | 31.Dec.2019 11:59 PM CET |