Researcher in Medical Image Analysis

Description of the workplace

As researcher in medical image analysis you will be placed at the Divison of Computer Vision and Machine Learning (CVML) at the Centre for Mathematical Sciences (https://maths.lu.se/). The Centre for Mathematical Sciences is an department affiliated with both the Faculty of Engineering (LTH) and the Faculty of Science at Lund University. Within CVML, there are several senior researchers as well as approximately 20 doctoral students. Research in the 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 basic research in computer vision, image analysis, machine learning, and artificial intelligence, as well as a track record of translating research results into practical applications for end-users

Work duties

CVML needs to hire a researcher for a limited period within the field of medical image analysis to participate in ongoing research projects and supervision of doctoral students, as well as assist in teaching at an basic and advanced level, for example, in the course of Medical Image Analysis and master thesis supervision.

The responsibilities include:

Research in the subject area of the announcement, including the development of deep neural networks for the analysis of medical data within ongoing research projects. Teaching at the undergraduate, advanced, and doctoral levels (up to 20% of full-time). Supervision doctoral students and master thesis work. Assisting in seeking external research funding. Collaboration with industry and society within ongoing research projects. Administrative tasks related to the above responsibilities are included. Opportunities for participation in higher education pedagogical competence development will be provided.

Qualifications

Requirements for the position are:

• You have a doctoral degree in mathematics.
• You have excellent proficiency in English, both spoken and written.
• You have extensive experience in research involving the application of machine learning methods and deep neural networks to medical image data.
• You have documented experience in collaboration with physicians or other researchers in medicine or with clinical staff.
• Experience in supervising thesis projects and doctoral students.
• You have significant experience with development environments for deep neural networks such as TensorFlow, Keras, PyTorch, or similar.

Consideration will also be given to demonstrated good collaborative skills, drive, and independence, as well as how the applicant's experience and competence complement and strengthen ongoing research at  and how they can contribute to its development.

Additional requirements:

• Experience in teaching at the undergraduate or advanced level.
• Successful experience in seeking external research funding.
• Experience in one or more of the following application areas: Pathology such as Gleason grading of prostate cancer, Radiology in the detection of cardiovascular diseases, detection of breast cancer, or prediction of Alzheimer's disease, and Dermatology such as the classification of skin cancer.
• Experience with various imaging modalities such as histopathological images from bright-field microscopy or digital scanning, conventional or modern ultrasound techniques, as well as CT or SPECT.
• Industry experience in a relevant area for the announcement.

We offer

Lund University is a public authority which means that employees get particular benefits, generous annual leave and an advantageous occupational pension scheme. It is advisable to enter information on what your unit specifically can offer as a workplace. Read more on the University website about being a Lund University employee Work at Lund University. https://www.lunduniversity.lu.se/about-university/work-lund-university 

Further information

The position commences on June 1, 2024, or at an agreed-upon date, and lasts for a maximum of one year. The employment will be full-time (100%).

Inquiries about the position can be made to the Head of Division for CVML, Niels Chr Overgaard (niels_christian.overgaard@math.lth.se).

How to apply

Applications are to be submitted via the University’s recruitment system. The application should include a CV and a personal letter justifying your interest in the position and how it matches your qualifications. The application should also include a degree certificate or equivalent and any other document to which you would like to draw attention (copies of grade transcripts, details of referees, letters of recommendation, etc.)”  

Welcome to apply!