Bioinformatician in Clinical Genetics Part-time NEW

Bioinformatician in Clinical Genetics

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.

At the Division of Clinical Genetics, Department of Laboratory Medicine, we are seeking a bioinformatician to work on developing classification algorithms for gene expression data in the field of hematological malignancies. The project focuses on developing and evaluating classification algorithms based on large datasets from RNA sequencing of blood cancer cells, with the aim of improving clinical diagnostics.

The research group is led by Professor Thoas Fioretos and consists of approximately ten employees with expertise in gene expression analysis, single-cell analysis, bioinformatics, and functional and mechanistic studies of hematological malignancies. The group is international, works in an interdisciplinary manner, and has established collaborations with other research groups, healthcare providers, and the life sciences industry.

We are now seeking a bioinformatician with very strong knowledge of machine learning and statistical analysis, as well as documented experience working with gene expression data in the field of hematological malignancies. The work is carried out both independently and in close collaboration with the other members of the group, including bioinformaticians and PhD students.

As a workplace, we value a positive working environment characterized by respect, consideration, and an open collaborative atmosphere.

Lund University is a government authority, which means that you will receive special benefits, generous annual leave, and an advantageous occupational pension. We also have a flexible working hours agreement that provides good opportunities for work-life balance.

You will be part of a team of bioinformaticians and PhD students developing methods to improve the clinical diagnosis of hematological malignancies through the analysis of gene expression data. Your duties will include developing bioinformatics analysis tools, applying and further developing machine learning-based classification algorithms, and evaluating whether neural networks can improve classification performance. As the research is data-driven, the work may also involve the development and application of other bioinformatics, mathematical, and statistical methods.

Requirements for the position are:

• PhD degree in bioinformatics, computer science, physics, mathematics, or another relevant technical or scientific field
• Very strong knowledge and documented experience in programming, data analysis, statistical modelling, and machine learning
• Documented experience developing and evaluating machine learning models based on gene expression data or other high-dimensional biological data within the field of hematological malignancies
• Excellent ability and documented experience working independently as well as in interdisciplinary teams involving multiple collaborators
• Excellent ability to communicate in Swedish and English, both verbally and in writing

Additional qualifications are:

• Experience with Python-based machine learning tools and methods for model optimisation, validation, and explainable machine learning
• Experience developing or evaluating neural networks for the classification of biological or clinical data
• Experience working in a larger interdisciplinary research group and experience writing scientific texts and presenting scientific results

The position is a fixed-term special employment (SÄVA) at 50% of full-time for 12 months, with a desired start date of September 1, 2026, or as agreed.

Applications must be submitted through the University's recruitment system. The application should include a cover letter explaining why you are interested in the position and how it matches your qualifications. The application should also include a CV, degree certificate or equivalent, and any other documents you wish to submit (copies of transcripts, reference details, letters of recommendation, etc.)

The University applies individual salary setting. You are welcome to state your salary expectations in your application.