Norges Teknisk-naturvitenskapelige Universitet Ntnu

Trondheim

Mattijs Elschot

Professor

<h2>This is NTNU</h2><p>NTNU is a broad-based university with a technical-scientific profile and a focus in professional education. The university is located in three cities with headquarters in Trondheim.</p><p>At NTNU, 9,000 employees and 43,000 students work to create knowledge for a better world.</p><p>You can find more information about working at NTNU and the application process<a href="https://www.ntnu.edu/vacancies/" rel="nofollow"> here.</a></p><p>   </p> Video: https://youtu.be/Xt-yHCN5QS0<br /><h2>About the Job</h2><p>We have a vacancy for a temporary researcher position. </p><p>This is a 100 % position for 1 year, starting January 2026 with the possibility of extension. You will be working on the FLIP.AI project (<a href="https://www.ntnu.edu/isb/flipai" rel="nofollow">https://www.ntnu.edu/isb/flipai</a>), an ongoing project on federated machine learning for improving prostate cancer diagnosis with artificial intelligence (AI). The project is funded by the Norwegian Cancer Society. In this project, we develop, validate, and test federated AI for medical imaging tasks like organ segmentation and prostate cancer detection. Your responsibilities include continuing the technical development of our Federated Learning framework, and benchmarking its performance for multi-modal, multi-organ segmentation on existing data sets. Experience with developing medical imaging AI and federated learning frameworks is expected. </p><p>The researcher will be part of CIMORe, which is a multidisciplinary research group working within the field of personalized cancer medicine. For more information about the research group, please visit the following web page: <a href="https://www.ntnu.edu/isb/mr-cancer" rel="nofollow">https://www.ntnu.edu/isb/mr-cancer</a>. The position offers challenging and varied tasks in an environment characterized by active, committed and skilled employees.</p><p>Your immediate leader is Professor Mattijs Elschot.</p><br /><h2>Duties of the position</h2><ul><li>Technical development of a federated learning framework for multi-modal image segmentation </li><li>Training and testing of federated AI for medical image segmentation tasks </li><li>Interdisciplinary interaction with local, national and international researchers, clinicians, and IT-staff</li><li>Writing, publishing and communication of results to academic peers, clinical users and the general public</li></ul><br /><h2>Required selection criteria</h2><ul><li>You must have completed a Norwegian doctoral degree or corresponding foreign doctoral degree recognized as equivalent to a Norwegian PhD in computer science. </li><li>Excellent programming skills in Phyton</li><li>Proficiency with PyTorch and/or TensorFlow</li><li>Strong experience with deep learning to solve medical imaging / computer vision problems, documented by research papers or a PhD dissertation</li><li>Strong experience with federated machine learning, documented by research papers or a PhD dissertation</li><li>Excellent English skills, spoken and written</li><li>Possibility to start in January 2026</li></ul><br /><h2>Preferred selection criteria</h2><ul><li>A PhD degree on the topic of federated machine learning or other forms of distributed machine learning</li></ul><br /><h2>Personal characteristics</h2><ul><li>Ability to work both independently and in a team</li><li>Excellent communication skills</li><li>Motivated, resourceful and proactive</li></ul><br /><h2>We offer</h2><ul><li>exciting and stimulating tasks in a strong international academic environment</li><li>an open and <a href="https://innsida.ntnu.no/wiki/-/wiki/Norsk/Inkluderende&#43;arbeidsliv" rel="nofollow">inclusive work environment</a> with dedicated colleagues</li><li>favourable terms in the <a href="https://www.spk.no/en/" rel="nofollow">Norwegian Public Service Pension Fund</a></li><li><a href="https://innsida.ntnu.no/wiki/-/wiki/English/Benefits&#43;and&#43;discounts" rel="nofollow">employee benefits</a></li></ul><br /><h2>Salary and conditions</h2><p>The gross salary for the position of researcher (code 1109) is normally remunerated at gross from NOK 579 700 – 725 500 before tax per year, depending on qualifications and seniority. From the salary, 2% is deducted as a contribution to the Norwegian Public Service Pension Fund,</p><p>The engagement is to be made in accordance with the regulations in force concerning State Employees and Civil Servants, and the acts relating to Control of the Export of Strategic Goods, Services and Technology. Candidates who by assessment of the application and attachment are seen to conflict with the criteria in the latter law will be prohibited from recruitment to NTNU</p><p>The position is subject to external funding.</p><p>It is a prerequisite that you can be present at and accessible to the institution daily. </p><br /><h2>About the application</h2><p>The application and supporting documentation must be in English.</p><p>Please note that your application will be considered based solely on information submitted by the application deadline. You must therefore ensure that your application clearly demonstrates how your skills and experience fulfil the criteria specified above.  If, for any reason, you have taken a career break or have had an atypical career and wish to disclose this in your application, the selection committee will take this into account, recognizing that the quantity of your research may be reduced as a result. </p><p>The application must include: </p><ul><li>CV, certificates and diplomas </li><li>Academic works - published or unpublished - that you would like to be considered in the assessment (up to 10 works)  </li><li>Names and contact information for three relevant referees <br /> </li></ul><p>Joint work will also be considered. If it is difficult to identify your specific input to a joint project, you must include evidence of your contributions.  </p><p>In the assessment of the best qualified applicant, we will emphasize education, experience and personal suitability as well as your motivation for the position. </p><p>NTNU is committed to following evaluation criteria for research quality according to<a href="http://www.ascb.org/wp-content/uploads/2017/07/sfdora.pdf" rel="nofollow"> The San Francisco Declaration on Research Assessment - DORA. </a>This means that we pay special attention to the quality and professional breadth of these works. We also consider experience from research management and participation in research projects. We place great emphasis on your scientific work from the last five years.</p><br /><h2>General information</h2><p>NTNU believes that inclusion and diversity is a strength. We want our faculty and staff to reflect Norway’s culturally diverse population and we continuously seek to hire the best minds. This enables NTNU to increase productivity and innovation, improve decision making processes, raise employee satisfaction, compete academically with global top-ranking institutions and carry out our social responsibilities within education and research. NTNU emphasizes accessibility and encourages qualified candidates to apply regardless of gender identity, ability status, periods of unemployment or ethnic and cultural background.  </p><p>NTNU is working actively to increase the number of women employed in scientific positions and has a number of <a href="https://www.ntnu.edu/genderequality" rel="nofollow">resources to promote equality.</a> </p><p>The city of Trondheim is a modern European city with a rich cultural scene. Trondheim is the innovation capital of Norway with a population of 200,000. The Norwegian welfare state, including healthcare, schools, kindergartens and overall equality, is probably the best of its kind in the world. Professional subsidized day-care for children is easily available. Furthermore, Trondheim offers great opportunities for education (including international schools) and possibilities to enjoy nature, culture and family life and has low crime rates and clean air quality.</p><p>----------------------</p><p>As an employee at NTNU, you must at all times adhere to the changes that the development in the subject entails and the organizational changes that are adopted. </p><p>A public list of applicants with name, age, job title and municipality of residence is prepared after the application deadline. If you want to reserve yourself from entry on the public applicant list, this must be justified. Assessment will be made in accordance with <a href="https://lovdata.no/dokument/NL/lov/2006-05-19-16/KAPITTEL_3#%C2%A725" rel="nofollow">current legislation</a>. You will be notified if the reservation is not accepted.</p><p>If you have any questions about the position, please contact Mattijs Elschot, email <a href="mailto:mattijs.elschot&#64;ntnu.no" rel="nofollow">mattijs.elschot&#64;ntnu.no</a>. </p><p>If you have any questions about the recruitment process, please contact Helene Berri, e-mail: <a href="mailto:helene.b.berri&#64;ntnu.no" rel="nofollow">helene.b.berri&#64;ntnu.no</a>  </p><p>If you think this looks interesting and in line with your qualifications, please submit your application electronically via jobbnorge.no with your CV, diplomas and certificates attached. Applications submitted elsewhere will not be considered. Upon request, you must be able to obtain certified copies of your documentation. </p><p><strong>Application deadline: 23.10.2025</strong></p><br />

Researcher in federated machine learning for medical imaging