Do you want to contribute to improving human health?
This position is part of a joint collaboration between the two largest
research programs in Sweden, the Wallenberg AI, Autonomous Systems and
Software Program (WASP) and the SciLifeLab and Wallenberg National Program
for Data-Driven Life Science (DDLS), with the ultimate goal of solving
ground-breaking research questions across disciplines.
We are a translational group with a strong cross-disciplinary collaboration
between breast radiology at Karolinska Institutet (KI) and computer science
at the Royal School of Engineering (KTH) and SciLifeLab. The members at KTH
are mainly responsible for the development of algorithms, and the members at
KI are mainly responsible for directing the initial data curation and the
later evaluation of algorithm performance. In addition, we are exploring
aspects of AI governance, including setting up a national platform for
retrospective validation of AI algorithms in mammography screening and to
develop early-warning methods to detect when the AI predictions might no
longer be trustworthy.
We now seek to strengthen our internationally leading clinical research group
at KI with a postdoctoral researcher within the field of biostatistics applied
to clinical studies of AI in breast cancer imaging.
Your research will consist of mainly two different topics. The first topic
concerns the development and evaluation of in-house AI algorithms. One of your
responsibilities will be to contribute with statistical competence in the
development process of AI algorithms, helping the computer scientists with
appropriate evaluation methods and with study design. You will also take
responsibility for the retrospective evaluation of the developed algorithms in
our data and in data from international collaborators. The second topic
concerns the real-world follow-up of the performance and trustworthiness of AI
algorithms in general, both in-house and commercial ones. You would evaluate
different approaches to detect when a “black-box” AI algorithm may no longer
be trustworthy, such as detecting distributional shifts. You might also
explore the use of 3D-printed phantoms as reference standards for daily
quality control of installed AI algorithms.
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 are looking for a person who is highly motivated, hard-working, self-
directing and creative. You should have a PhD degree with focus on statistics,
biostatistics, statistical machine learning, or a closely related field. Since
we are working across disciplines and also have several international
collaborators you should have excellent communication and collaboration
skills. A track record of clinically oriented publications is considered an
advantage. Experience of research in the cancer or imaging field would be
especially beneficial. You should have experience with writing advanced
scripts in a common statistical software package such as R, and be proficient,
or willing to become proficient in Python scripting. Experience with a deep
learning framework (TensorFlow, PyTorch, or JAX). You should have excellent
communications and scientific writing skills.
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.
The DDLS initative
The SciLifeLab and Wallenberg National Program for Data-Driven Life Science
(DDLS) is a 12-year initiative that focuses on data-driven research, within
fields essential for improving the people ́s lives, detecting and treating
diseases, protecting biodiversity and creating sustainability. The programme
will train the next generation of life scientists and create a strong
computational and data science base. The program aims to strengthen national
collaborations between universities, bridge the research communities of life
sciences and data sciences, and create partnerships with industry, healthcare
and other national and international actors. Read more:
https: // www. scilifelab.se/data-driven.
An employment application must contain the following documents in English or
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 apply at the latest January 17.
The application is to be submitted through the Varbi recruitment system.
Want to make a difference? Join us and contribute to better health for
|Type of employment
||Temporary position longer than 6 months
|First day of employment
||As per agreement
|Number of positions
|Last application date
||16.Jan.2022 11:59 PM CET