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Vicente Pelechano

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Postdoctoral studies in Computational and Structural RNA Biology (scholarship) Karolinska Institutet in Sweden

Degree Level

Postdoc

Field of study

Computer Science

Funding

Tax-free scholarship paid for twelve months at a time, paid out on a six months basis; maximum duration up to two years within a four-year period after the doctorate.

Deadline

Nov 23, 2026

Country flag

Country

Sweden

University

Karolinska Institutet

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Keywords

Computer Science
Biology
Predictive Modeling
Structural Biology
Computational Biology
Rna Biology
Yeast Biology
Statistics
Bioinformatic
ML

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About this position

Vicente Pelechano’s Research Group at Karolinska Institutet is offering a postdoctoral scholarship in computational and structural RNA biology. The project sits at the intersection of RNA biology, computational biology, and genome-wide method development, with a strong emphasis on how RNA sequence and structure shape gene regulation and cellular phenotypes.

The successful candidate will work on understanding how variation in untranslated regions, especially alternative 3′ UTR isoforms and natural or engineered UTR sequence changes, alters RNA structure and influences mRNA fate. The research combines structure prediction and modelling with genome-wide experimental datasets in complementary human and yeast systems, aiming to build structure-aware predictive models of RNA regulation.

The position is embedded in an interdisciplinary and international research environment within the Department of Microbiology, Tumor and Cell Biology (MTC) at Karolinska Institutet. The lab is based at SciLifeLab on the Karolinska Institutet campus, giving access to advanced instrumentation and core facilities. The group’s work bridges experimental and computational approaches to fundamental biological questions with medical relevance.

The project offers the chance to carry out original research in RNA structure, post-transcriptional regulation, and computational analysis while developing both experimental and computational expertise. The role also involves scientific communication, teamwork, and interaction with researchers from diverse backgrounds in a highly collaborative setting.

Funding details

Tax-free scholarship paid for twelve months at a time, paid out on a six months basis; maximum duration up to two years within a four-year period after the doctorate.

What's required

Applicants must have a doctorate, or a foreign degree deemed equivalent to a doctorate, and must be foreign researchers who have not been resident in Sweden or carried out all or part of their academic education at KI or another Swedish institution. Applicants who have not yet completed the doctorate may apply if all requirements for the degree will be met before the intended start date. Candidates should have a strong background in computational biology, RNA biology, RNA structure or a related field; documented experience in computational analysis of gene regulation; high-quality publications; excellent spoken and written English; experience interpreting biological data and developing hypotheses; strong interpersonal skills and ability to work in a team. Required technical skills include computational analyses and bioinformatics using Python and/or R, and knowledge of RNA biology and post-transcriptional gene regulation. Preferred experience includes RNA structural biology, RNA structure prediction, large-scale sequence or functional genomics datasets, machine learning or predictive modelling, structure-guided sequence design, integration of computational and experimental data, reproducible workflows, and yeast genetics/genomics/RNA biology.

How to apply

Prepare an English or Swedish application with a complete CV, full publication list, and a one-page summary of current work. Submit the application through the Varbi recruitment system using the provided application link.

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Professors

Professor at Karolinska Institutet

University Name
Country flag

Sweden

Research Interests

Statistics

Computational Biology

Rna Biology

Predictive Modeling

Structural Biology