DDLS industrial PhD position
We are announcing a position for a Data-Driven Life Science (DDLS) PhD student in data-driven precision medicine and diagnostics. To be a doctoral student means to devote oneself to a research project under supervision of experienced researchers and following an individual study plan. A doctoral degree corresponds to four years of full-time study.
This is an industry PhD project which is a collaboration between the Karolinska Institute, SciLifeLab and Ribocure Pharmaceuticals AB. The PhD student will be employed by Ribocure Pharmaceuticals AB but admitted to PhD studies at the Karolinska Institute. The studies will primarily take place at the Karolinska Institute and SciLifeLab in Stockholm, with frequent research internships at Ribocure Pharmaceuticals AB in Gothenburg.
We offer a creative and inspiring environment full of expertise and curiosity. The Karolinska Institute 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 the Karolinska Institute, we conduct successful medical research and hold the largest range of medical education in Sweden. As a doctoral student you are offered an individual research project, a well-educated supervisor, a vast range of elective courses and the opportunity to work in a leading research group. Tbe Karolinska Institute collaborates with prominent universities from all around the world, which ensures opportunities for international exchanges.
Ribocure Pharmaceuticals AB, based in Gothenburg, is a clinical‑stage biotech company developing innovative siRNA‑based therapies. Our research focuses on areas with high unmet medical need, including cardiovascular, metabolic, liver, and kidney diseases. We have access to a strong and vertically integrated platform in oligonucleotide research, spanning from early discovery to clinical development. Our goal is to turn cutting‑edge science into new medicines for patients. The PhD project will be embedded in a close collaboration with Ribocure, providing the candidate with valuable exposure to industrial drug development, insight into how academic discoveries are translated into medicines, and experience of working at the interface between fundamental research and therapeutic innovation.
Project description
Project title: “RIBO-LINC: Linking data-driven solutions and RNA innovation for liver and cardiometabolic health”.
An exciting opportunity is available to join a cutting-edge project at the interface of AI, multi-omics, and RNA therapeutics, aiming to transform precision medicine for cardiometabolic and liver diseases. Current therapeutic strategies largely operate at the gene level, overlooking the functional diversity generated by alternative splicing. This project addresses this critical gap by developing data-driven approaches to identify and prioritize isoform-specific therapeutic targets, enabling a new level of precision in RNA-based treatments. The project will combine large-scale multi-omics integration with advanced machine learning, including artificial neural networks, to predict disease-relevant splice variants across cardiometabolic diseases. By leveraging extensive meta-cohort and perturbation datasets, the work aims to uncover isoform-level regulatory mechanisms and guide the development of next-generation RNA therapeutics with improved specificity and reduced off-target effects. Importantly, computational predictions will be directly linked to experimental evaluation of GalNAc-conjugated RNA therapeutics. This position offers a unique opportunity to work in a highly interdisciplinary environment, contributing to the development of transformative therapies at the forefront of AI-driven biomedical research.
Qualification requirements
To be admitted to postgraduate education, the applicant must meet the general and specific entry requirements. The qualification requirements must be met by the deadline for applications.
You meet the (A) general entry requirements if you:
- have been awarded a second-cycle/advanced/master qualification (i.e. master degree), or
- have satisfied the requirements for courses comprising at least 240 credits of which at least 60 credits were awarded in the advanced/second-cycle/master level, or
- have acquired substantially equivalent knowledge in some other way in Sweden or abroad.*
Follow the instructions on the web page Entry requirements (eligibility) for doctoral education.
*If you claim equivalent knowledge, follow the instructions on the web page Assessing equivalent knowledge for general eligibility for doctoral education.
To meet the (B) specific entry requirements, the applicant must have
- credits in Life Science, Computer Science Mathematics, Physics or Bioinformatics or alike, including a 30 credit Degree Project (thesis).
- proficiency in English equivalent to the course English B/English 6 at Swedish upper secondary school. Follow the instructions on the web page English language requirements for doctoral education.
Verification of your documents: The Karolinska Institute checks the authenticity of your documents and reserves the right to revoke admission if supporting documents are discovered to be fraudulent. Submission of false documents is a violation of Swedish law and is considered grounds for legal action.
Additional preferred qualifications:
- Prior experience with bioinformatics workflows and analysis of large-scale multi-omics datasets (e.g., RNA-seq, proteomics, long-read sequencing).
- Familiarity with machine learning approaches, particularly artificial neural networks, and their application to biological data.
- Experience with workflow management systems (e.g., Snakemake, Nextflow) and reproducible data processing pipelines.
- Knowledge of transcriptomics and alternative splicing analysis, including isoform-level quantification tools.
- Programming skills in R and/or Python, with experience in data integration and statistical analysis.
- Exposure to RNA therapeutics or functional genomics approaches is an advantage.
- Strong interest in interdisciplinary research combining computational biology with experimental validation.
Selection
The selection among eligible candidates will be based on their ability to successfully complete the PhD studies. Key criteria include analytical thinking, the capacity to work independently and collaboratively, as well as creativity, initiative, and a strong interest in interdisciplinary research.
The assessment will be based on:
- Technical Expertise: Documented experience in R and/or Python, with proficiency in bioinformatics and analysis of multi-omics datasets (e.g., RNA-seq, proteomics, long-read sequencing). Familiarity with machine learning approaches, particularly neural networks, and experience with workflow management systems (e.g., Snakemake, Nextflow). Knowledge of transcriptomics and alternative splicing analysis.
- Academic and Research Excellence: Demonstrated high-quality academic performance, including strong grades and relevant degree projects. Prior research experience in computational biology, functional genomics, or related fields will be highly valued.
- Soft Skills and Research Attributes: Excellent written and oral communication skills in English, strong analytical and problem-solving abilities, and the capacity to work both independently and in collaborative, interdisciplinary environments. Creativity, initiative, and a structured approach to complex data analysis are essential.
- Motivation and Fit: A well-articulated motivation letter describing the candidate’s interest in AI-driven multi-omics integration and RNA therapeutics. The candidate should demonstrate enthusiasm for bridging computational and experimental research. Final evaluation will include interviews and reference checks to assess overall fit and potential.
Terms and conditions
The doctoral student will be employed at Ribocure Pharmaceuticals with affiliation to Karolinska Institute on a doctoral studentship maximum 4 years full-time.
Application process
Submit your application and supporting documents through Ribocure Pharmaceuticals AB recruitment system. We prefer that your application is written in English, but you can also apply in Swedish.
Deadline to apply is August 2nd 2026.
Your application must contain the following documents:
- A personal letter and a curriculum vitae
- Degree projects and previous publications, if any
- Any other documentation showing the desirable skills and personal qualities described above
- Documents certifying your general eligibility (see A above)
- Documents certifying your specific eligibility (see B above)
DDLS and the SciLifeLab
SciLifeLab is a national center for molecular biosciences with a focus on health and environmental research. The center combines frontline technical expertise with advanced knowledge of translational medicine and molecular bioscience. SciLifeLab is a national resource hosted by Karolinska Institutet, KTH Royal Institute of Technology, Stockholm University and Uppsala University. The center also collaborates with several other universities.
Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes to human health and global ecosystems. The SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS) aims to recruit and train the next generation of data-driven life scientists and to create globally leading computational and data science capabilities in Sweden. The program is funded with a total of 3.3 billion SEK over 12 years from the Knut and Alice Wallenberg (KAW) Foundation.
In 2026 the DDLS Research School will be expanded with the recruitment of 25 academic and 7 industrial PhD students. During the course of the DDLS program more than 260 PhD students and 200 postdocs will be part of the Research School. The DDLS program has four strategic research areas: cell and molecular biology, evolution and biodiversity, precision medicine and diagnostics, epidemiology and biology of infection. For more information, please see
https://www.scilifelab.se/data-driven/ddls-research-school
The future of life science is data-driven. Will you be part of that change? Then join us in this unique program!
Useful links
Claudia Kutter Research group at the Karolinska Institute and SciLifeLab
DDLS Research School
For any questions regarding the position please contact:
Julia Grönros, PhD
Project Director External Innovation
julia.gronros@ribocure.com
Ribocure Pharmaceuticals AB
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