Doctoral student in Applied Mathematics with a focus on Machine Learning for Medical Imaging Full-time NEW

Doctoral Student in Applied Mathematics with a Focus on Machine Learning for Medical Imaging

Lund University was founded in 1666 and is repeatedly ranked among the world's top universities. The University has around 46,000 students and 8,500 staff based in Lund, Helsingborg, and Malmö. We are united in our efforts to understand, explain, and improve our world and the human condition.

The position will be placed at the Division of Computer Vision and Machine Learning at the Centre for Mathematical Sciences. The Centre for Mathematical Sciences is an institution affiliated with both the Faculty of Engineering (LTH) and the Faculty of Science at Lund University.

Within the division of Computer Vision and Machine Learning, there are several senior researchers and approximately 20 doctoral candidates. Research in this field began in the mid-1980s and currently encompasses (i) geometry and computer vision, (ii) medical image analysis, and (iii) machine learning and artificial intelligence. The group has extensive experience in both fundamental research and applied collaborations.

The position is part of the strategic research initiative ELLIIT and is carried out in close collaboration with Linköping University. The project is jointly supervised, with Associate Professor Anders Eklund (Linköping University) acting as co-supervisor. The project also includes collaboration with the radiology and medical imaging research environment in Lund.

As a doctoral student, you are both admitted as a student and employed at Lund University. As a doctoral student, you will be trained in a scientific approach. In short, you will be trained to think critically and analytically, to solve problems independently using the right methods, and to develop an awareness of research ethics. In addition, you will have the opportunity to work on projects, to develop your leadership and pedagogical skills. Throughout your studies, you will be guided by supervisors. Doctoral studies end with a thesis and a doctoral degree.

More about being a doctoral student at LTH on lth.se.

The research subject is applied mathematics. The project focuses on computer vision and machine learning, with a particular emphasis on deep learning methods for medical image analysis and multimodal data integration.

You will primarily devote yourself to your doctoral programme, which includes participation in research projects, third cycle courses, seminars, and conferences. You will work in a research environment focused on computer vision and machine learning for medical imaging, and you will contribute to method development, evaluation, and scientific dissemination. The dissertation work will involve development of new methods, experimental design, data processing, programming and implementation, writing scientific articles, and presenting results at international conferences.

The work duties include:

• Development of hybrid CNN-transformer architectures for medical image analysis
• Investigation of attention mechanisms and architectural design choices
• Development of multimodal models integrating imaging and patient data
• Design of methods handling missing or noisy modalities
• Implementation and evaluation on medical imaging datasets
• The duties also include participation in teaching and other departmental work (however, a maximum of 20% of working hours).

To be eligible for admission and employment as a doctoral student, you must fulfil the requirements below.

A person meets the general admission requirements for third-cycle courses and study programmes if he or she:

• has been awarded a second-cycle qualification, or
• has satisfied the requirements for courses comprising at least 240 credits of which at least 60 credits were awarded in the second cycle, or
• has acquired substantially equivalent knowledge in some other way in Sweden or abroad

The higher education institution may permit an exemption from the general entry requirements for an individual applicant, if there are special grounds. Ordinance (2010:1064).

A person meets the specific admission requirements if he or she has:

• at least 90 credits of relevance to the subject area, of which at least 45 credits are from the second cycle.

Finally, the student must be judged to have the potential to complete the programme.

Exemptions from the admission requirements may be granted by the dean of LTH.

In order to complete the doctoral programme in question, the following are also required:

• Documented subject knowledge relevant to the project, such as mathematics, applied mathematics, computer vision, machine learning, deep learning, or medical image analysis.
• Experience of programming and method development relevant to machine learning, deep learning, computer vision, or medical image analysis.

Personal qualities required to perform the duties and complete the doctoral programme include initiative, independence, structure, persistence, and the ability to collaborate effectively in a research environment.

• Good ability to work independently and to formulate and tackle research problems.
• Good written and oral communication skills.
• Good ability to cooperate.
• Very good knowledge of English, spoken and written.
• Good programming skills in Python and/or C++.

For the doctoral programme in question, the following are considered as other qualifications:

• Knowledge of computer vision, deep learning, medical image analysis, transformer-based models, or multimodal learning is considered an advantage.
• Experience with machine learning frameworks such as PyTorch or TensorFlow, and experience of working with medical imaging datasets, are considered an advantage.
• Collaborative skills, initiative, and independence, and how the applicant's experience and competencies are deemed to contribute to successful completion of the doctoral programme, are considered an advantage.
• Research or professional experience of relevance to the thesis project is considered an advantage.

Lund University is a public authority which means that employees get particular benefits, generous annual leave and an advantageous occupational pension scheme. At the Division of Computer Vision and Machine Learning, you will be part of a dynamic and internationally recognised research environment with strong expertise in computer vision, machine learning, and artificial intelligence. The group offers close collaboration with senior researchers and other doctoral students, access to modern computational resources, and an active seminar and collaboration culture. The environment combines fundamental research with applied projects and provides opportunities to engage with both academic and industrial partners, as well as interdisciplinary collaborations with medical imaging and radiology groups.

More about working at Lund University on lu.se.

The employment is a fixed-term, full-time position starting in early autumn 2026, but no later than 1 December 2026. Third cycle studies at LTH consist of full-time studies for 4 years. In the case of teaching and other departmental duties, the employment is extended accordingly. Doctoral studentships are regulated in the Higher Education Ordinance (1993:100), chapter 5, 1-7 §§.

More about terms of employment for doctoral students on Lund University's Staffpages.

Applications shall be written in English and include:

• CV and a cover letter stating the reasons why you are interested in the doctoral programme/employment and in what way the research project corresponds to your interests and educational background.
• Copies of issued study certificates and/or awarded degree certificates. These must confirm that you meet the general and specific admission requirements for the doctoral programme and show that you have the subject knowledge required for the doctoral programme project.
• Other documents you wish to be considered (grade transcripts, contact information for your references, letters of recommendation, etc.)

We welcome your application.