The research group led by Professor Thomas Perlmann is focused on how specific cell types of the central nervous system are generated and how they are maintained. Our lab is mostly interested in midbrain dopaminergic neurons. We use cutting-edge techniques to study the signaling and transcriptional regulation that govern the specification, differentiation and maintenance of these cells. Our studies have resulted in the identification of several transcription factors with key roles in these processes. The projects are focused on understanding functions in both early specification events during embryonic development and in the maintenance of dopaminergic neurons in the adult brain. Moreover, we are also interested in regenerative medicine in relation to Parkinson’s disease and other brain disorders.
In this role, the candidate will perform bioinformatics and statistical analyses across multiple research projects, including BCL-to-FASTQ conversion, demultiplexing, alignment, quality control, multi-omics integration, and interpretation of high-throughput sequencing data. The candidate will provide guidance on statistical methods, computational approaches, and study design to ensure robust and reproducible analyses. Responsibilities include developing and maintaining web-based tools for data exploration and sharing (e.g., Shiny, Plotly, CellxGene), supporting database infrastructure (e.g., MySQL), and building reproducible analysis workflows and software solutions. The candidate will collaborate closely with researchers from diverse backgrounds, contribute to data visualization and interpretation, and work with senior bioinformaticians and scientists to plan analyses and deliver high-quality results that support the lab’s research objectives.
We are seeking a motivated bioinformatician with a master’s degree in bioinformatics, computational biology, or a related field. The successful candidate will contribute to projects involving next-generation sequencing data, including single-cell RNA-seq, spatial omics, and multiomics. The role requires strong analytical and communication skills, the ability to work independently, and a commitment to producing reproducible research. Experience with machine learning, statistical analysis, Python, R, Linux, GitHub, Docker, Nextflow, and MySQL is required. Candidates should be comfortable working in Linux-based computing environments and supporting virtual machines and computational resources. Extensive experience with data preprocessing and analysis of single-cell, bulk RNA-seq, and multiomics datasets is essential. Familiarity with public biological databases, Python packaging, and PyPI is desirable. Experience with DNA sequencing, genome assembly, cDNA library preparation, spatial omics, or neuroscience is considered an advantage. Good written and spoken English is required.
A creative and inspiring environment with wide-ranging expertise and interests. Karolinska Institutet is one of the world's leading medical universities. Our vision is to pursue the development of knowledge about life and to promote a better health for all. At Karolinska Institutet, we conduct successful medical research and hold the largest range of medical education in Sweden. Karolinska Institutet is also a state university, which entitles you to several good benefits through our collective agreement. And you get to practice freely in our modern wellness facilities, where trained staff are on site.
Location: Solna
KI applies individual and differentiated salary setting in accordance with our collective agreements RALS and RALS-T.
The application is to be submitted through the Varbi recruitment system. In this recruitment, you will apply with your CV without a personal letter. Instead, you will answer some questions about why you are applying for the job in the application form.
Permanent position is initiated by a six months trial period.
Anställningsform: tillsvidareanställning | Anställningens omfattning: heltid | Antal lediga befattningar: 1 | Sysselsättningsgrad: 100% | Ort: Stockholm | Län: Stockholms län | Land: Sweden | Referensnummer: STÖD 2-2490/2026 | Kontakt: Thomas Perlmann , Thomas Perlmann , | Facklig företrädare: Bodil Moberg , OFR/ST , Bodil Moberg , OFR/ST , Elizabeth Valenzuela, SEKO , Elizabeth Valenzuela, SEKO , Björn Andersson, SACO , Björn Andersson, SACO , | Publicerat: 2026-06-08 | Sista ansökningsdag: 2026-06-30
