1-2 Postdoctoral position in computational pathology and computer vision - Hiring in process/Finished, not possible to apply

Do you want to contribute to top quality medical research?

Your mission

This postdoctoral project is focused on development and validation of deep learning models and image processing methodologies for cancer histopathology image data. Machine learning and deep learning techniques are central in this computational pathology project aimed at improving cancer patient stratification. As a postdoctoral researcher you will be involved with implementation and evaluation of machine learning/deep learning models, and/or contribute to development of new methodologies and strategies in the domain. The project is based on unique and large in-house datasets. The role would suit applicants who are interested in developing a career in the intersection of machine learning, epidemiology and medical sciences. The Cancer Histopathology IMage Epidemiology (CHIME) project focus on large-scale studies that include histopathology image data and clinical information.

The predictive medicine group is focused on application of machine learning and AI for development and validation of predictive models for biomedical applications, with a particular interest in cancer precision medicine and computational pathology. Our research is based on large and high-dimensional datasets across multiple modalities, including molecular, clinical and medical imaging data.

This is a role of 1 year with possibility of extension for 1 year.

Your profile

Qualified to be employed as a postdoctor is one who has obtained a doctorate or has equivalent scientific competence. Applicants who have not completed a doctorate at the end of the application period may also apply, provided that all requirements for a completed degree are met before the (intended) date of employment. This must be substantiated by the applicant's main supervisor, director or equivalent.

We believe that you either have a strong background in computer vision research using deep learning and an interest in medical research, or that you have a background in quantitative medical research based on large datasets (e.g. biostatistics or epidemiology) with research experience in applied image analysis and deep learning. The successful candidate will join an interdisciplinary research team with strong collaboration with clinical departments and other national and international research groups.

To qualify, the applicant must hold, or expect to receive, a PhD degree (or equivalent) in a relevant subject and have a strong interest in quantitative aspects of medical research. Prior knowledge and research experience in a relevant quantitative field (e.g. machine learning, AI, epidemiology, computer vision, biostatistics, epidemiology) is required.

It is desirable that the candidate has prior experience from large-scale analysis of biomedical data and/or applied machine learning/deep learning/AI. Prior experience from cancer-related research or medical image research is desirable. The applicant should have previous knowledge and experience in programming in Python, and it is desirable that the applicant also has prior experience of working with common deep learning frameworks, such as Tensorflow/Keras or Pytorch. The applicant should be able to collaborate as part of a team as well as independently and be able to organize and prioritise his/her own tasks with minimal supervision. Excellent written and oral communication skills in English are required.

For further information please contact Associate Professor Mattias Rantalainen (email: mattias. rantalainen@ki.se)

What do we offer?

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 better health for all. At Karolinska Institutet, we conduct innovative medical research and provide the largest range of biomedical education in Sweden. Karolinska Institutet is a state university, which entitles employees to several benefits such as extended holiday and a generous occupational pension. Employees also have free access to our modern gym and receive reimbursements for medical care.

Location: Solna

Application

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

• A complete resumé, 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)

Welcome to appl!

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

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