Postdoctoral fellow in machine learning for medical image analysis

Thursday 12th September 2024

Contact Email for the Job Posting [email protected]
Organization Chalmers University of Technology
Location Gothenburg, Sweden
Title Postdoctoral fellow in machine learning for medical image analysis
URL https://www.chalmers.se/om-chalmers/arbeta-hos-oss/lediga-tjanster/?rmpage=job&rmjob=13028&rmlang=EN
Closing date Oct 12, 2024
Description Join our team working on developing state-of-the-art machine learning image analysis models to solve clinically important tasks focused on disease prediction and prognostication!
Project description
This position is focused on research in applications of image analysis in the biomedical area, e.g. developing automatic methods to interpret images from medical imaging systems. The project aims to develop models to evaluate, predict and prognosticate diseases, focusing on lung cancer mainly using computed tomography images (CT), and other medical imaging modalities such as x-ray, ultrasound, and nuclear medicine imaging. We aim to develop state-of-the-art methods for medical image analysis, based on key enabling techniques from machine learning, estimation, optimization, and mathematical modeling. Our research is highly multi-disciplinary and will be performed in close collaboration with medical researchers from the Sahlgrenska Academy at Gothenburg University and other medical institutions within Sweden and on the international scene.
The research group
The Computer Vision Group at the Department of Electrical Engineering conducts research in the field of automatic image interpretation and perceptual scene understanding. The group targets both medical applications, such as the development of new and more effective methods and systems for analysis, support, and diagnostics, as well as general computer vision applications including autonomously guided vehicles (particularly self-driving cars), image-based localization, structure-from-motion, and object recognition. The main research problems include mathematical theory, algorithms, and machine learning (deep learning) for inverse problems in artificial intelligence, as well as application to medical problems.
Main responsibilities
Your major responsibility as a postdoc is to perform your own research in a research group. The position may also include teaching on undergraduate and master's levels as well as supervising master's and/or PhD students to a certain extent. Another important aspect involves collaboration within academia and with society at large. The position is meritorious for future research duties within academia as well as industry/the public sector.
Your profile
To qualify for this position, you must hold a PhD or equivalent in Computer Vision, Machine Learning, Applied Mathematics or another related field, awarded no more than three years prior to the application deadline (according to the current agreement with the Swedish Agency for Government Employers). Exceptions from the 3-year limit can be made for longer periods resulting from parental leave, sick leave or military service*.
The position requires sound verbal and written communication skills in English. Swedish is not a requirement but Chalmers offers Swedish courses.
You are expected to be somewhat accustomed to teaching and to demonstrate good potential within research and education.
* The date shown in your doctoral degree certificate is the date we use, as this is the date you have met all requirements for the doctoral degree.
Contract terms
This postdoc position is a full-time temporary employment for two years.
We offer
Chalmers offers a cultivating and inspiring working environment in the coastal city of Gothenburg.
Read more about working at Chalmers and our benefits for employees.
Chalmers aims to actively improve our gender balance. We work broadly with equality projects, for example the GENIE Initiative on gender equality for excellence. Equality and diversity are substantial foundations in all activities at Chalmers.
Application procedure
The application should be marked with 20240373 and written in English. The application should be sent electronically and be attached as PDF-files, as below. Maximum size for each file is 40 MB. Please note that the system does not support Zip files.
CV: (Please name the document as: CV, Surname, Ref. number) including:
• CV, include complete list of publications
• Previous teaching and pedagogical experiences
• Two references that we can contact.
Personal letter: (Please name the document as: Personal letter, Family name, Ref. number)
1-3 pages where you:
• Introduce yourself
• Describe your previous research fields and main research results
• Describe your future goals and future research focus
Other documents:
• Attested copies of completed education, grades and other certificates.