Postdoctoral studies in computational pathology for precision medicine (scholarship)

Postdoctoral studies in computational pathology for precision medicine (scholarship) is available at The predictive medicine group, Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Sweden Feb 2022

General Info

Position: Postdoc

Fellowship/Scholarship: Karolinska Institutet Scholarships

 
No. of Positions: 1

Eligibile Nationals: All Nationals

Research Field: Artificial Intelligence, Biostatistics, Computer Science, Epidemiology, Machine learning

Joining Date: ASAP

Contract Period: 2 Years

Qualification Details

Scholarships for postdoctoral qualification can be established for foreign researchers who place their qualifications in Sweden. The purpose of scholarships for postdoctoral qualification is to promote internationalization and contribute to research qualification after a doctorate or equivalent. A scholarship for carrying out postdoctoral research can be granted for a maximum of two years within a four year period following the receipt of a doctoral degree or equivalent. To be eligible for a postdoctoral scholarship, the person must have obtained a doctorate or a foreign degree deemed to be equivalent to a doctorate. 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) start date of the post doctoral education.

The head of the department determines whether their previous training and scholarly qualifications correspond to a Swedish doctorate or higher.

Responsibilities/Job Description

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 someone with a PhD in computational pathology, alternatively someone with experience from medical image analysis and modern deep-learning methodologies. Prior understanding of cancer precision medicine and epidemiology is advantageous. The Cancer Histopathology IMage Epidemiology (CHIME) project focus on large-scale studies that include histopathology image data and clinical information.

We believe that you either have a PhD in AI-based computational pathology, or strong background in deep learning and image analysis with a an interest in medical research and precision medicine. The successful scholarship holder 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: [email protected])

How to Apply?

Application Method: Online Application
Ref. No.: STÖD 2-612/2022

Application Procedure

An 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)