Project assistant with focus on deep learning and image analysis

Lund University, Institutionen för immunteknologi

Lund University was founded in 1666 and is repeatedly ranked among the world’s top universities. The University has around 47 000 students and more than 8 800 staff based in Lund, Helsingborg and Malmö. We are united in our efforts to understand, explain and improve our world and the human condition.

Lund University welcomes applicants with diverse backgrounds and experiences. We regard gender equality and diversity as a strength and an asset.

Description of the workplace

The Department of Immunotechnology is dedicated to research in Life Science, including immunology, oncology, and hypersensitivity/allergy. Our modern premises are located at Medicon Village, which hosts academic researchers, Life Science companies and health care actors. Several key infrastructures are available here, including facilities for Spatial Omics, mass spectrometry, flow cytometry, and antibody engineering, as well as NBIS (National Bioinformatics Infrastructure Sweden) bioinformaticians. Application of advanced technology to address complex biomedical challenges has positioned the Department at the forefront of several research areas and generated multiple spin-off companies also located at Medicon Village. You will be part of a research team dedicated to developing precision medicine tools for cancer treatment, which relies on translational research of molecular and cellular processes in cancer.

Work duties and areas of responsibility

You will be part of a research group focusing on spatial tumor biology. We are mapping interactions between tumor and immune cells to understand immune response in tumors and how the immune system can be stimulated for improved treatment outcome. We work in multidisciplinary, translational projects to develop tools for precision medicine. Particularly, you will be responsible for developing prediction models for ovarian cancer. The work includes analysis of tissue images from multiplex immunofluorescence, graph-based image analysis and development of artificial neural networks. You will also work with analysis of spatial transcriptomics data. Documentation of code and workflows, compilation of data and communication of results to the research group and our collaborators are important aspects of your work.

Qualifications

Requirements for employment are:

Master’s education in bioinformatics
Extensive experience in bioinformatics and compiling of related documentation
Hands-on experience in deep learning methods
Hands-on experience from work in Python and Git
Experience in image analysis
Excellent written and oral English skills
Excellent collaboration and communication skills

Additional qualifications for the position are:

Experience of working in Qupath
Experience of working with large scale protein and/or RNA data
Experience from working in computational cluster environments
Experience in data analysis of patient material
Knowledge in tumor and/or immune markers

We will particularly consider personal qualities in regard to e.g., interpersonal skills, motivation, and independence.

Further information

The position is a fixed term position for 11 month at 100 % of full time and starting in 1st of September 2024 or by agreement.

How to apply

Applications are to be submitted via the University’s recruitment system. The application should include a personal letter justifying your interest in the position and how it matches your qualifications. The application should also include a CV, degree certificates 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.).

LTH is Lund University’s Faculty of Engineering. At LTH we educate people, build knowledge for the future and work hard for the development of society. We create space for brilliant research and inspire creative advancements in technology, architecture and design. We have nearly 10,000 students. Every year, our researchers – many of whom work in world-leading profile areas – publish around 100 theses and 2 000 scientific findings. In addition, many of our research and degree projects are transformed into innovations. Together we explore and create – to benefit the world.