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University of Copenhagen

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PhD in RNA Structure Computational Analysis and Neuronal RNA Localization University of Copenhagen in Denmark

Degree Level

PhD

Field of study

Computer Science

Funding

Fixed-term PhD position for 3 years. Salary, pension, and employment terms follow the Danish state academic agreement; starting monthly salary is approximately 31,850 DKK (about 4,260 EUR) plus pension, depending on seniority.

Deadline

Nov 4, 2026

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Country

Denmark

University

University of Copenhagen

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Keywords

Computer Science
Biomedical Engineering
Deep Learning
Biology
Computational Biology
Rna Biology
Neuropsychology
Medical Science
Rna-binding Proteins
Statistics
Bioinformatic
Transcriptomic
ML

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About this position

PhD position at the University of Copenhagen in RNA structure computational analysis and neuronal RNA sublocalization. The project is hosted in the Gorodkin lab at the Section for Health Data Science and AI, Department of Public Health, Faculty of Health and Medical Sciences.

The research focuses on building a predictive computational framework for understanding how polyadenylated RNAs localize in neurons, including mRNAs and long noncoding RNAs. The work integrates RNA sequence, RNA structure, RNA-binding protein interactions, and biological function to study localization in healthy, degenerating, and regenerating neurons. Methods mentioned include feature-based classifiers, machine learning, deep learning, convolutional neural networks, and transformers.

The project uses existing datasets such as Frac-seq and N-zip data, and aims to predict whether RNAs localize to neuronal cell bodies or neurites, identify sequence/structural features, and explore changes in neurodegeneration and regeneration, with relevance to ALS.

This is a 3-year full-time PhD position under the 5+3 scheme. The position starts on 2027-02-01. Salary and pension follow the Danish state academic agreement; the post states a starting monthly salary of approximately 31,850 DKK (about 4,260 EUR) plus pension, depending on seniority.

Eligibility highlights include an MSc in bioinformatics, computer science, computational biology, or a related area equivalent to a Danish master’s degree; strong Python and Linux/Unix skills; knowledge of algorithms, data analysis, machine learning, and basic RNA structure tools; and excellent English. Desirable experience includes RNA biology, RNA sequence/structure, RNA-protein interactions, deep learning, transcriptomics, CLiP, and omics data analysis.

Apply online in English by the deadline. The application must include a motivation letter mapping your experience to the listed requirements, CV, diploma/transcript, publications if any, and recommendations or an explanation if unavailable.

Funding details

Fixed-term PhD position for 3 years. Salary, pension, and employment terms follow the Danish state academic agreement; starting monthly salary is approximately 31,850 DKK (about 4,260 EUR) plus pension, depending on seniority.

What's required

Applicants must have completed an MSc degree in bioinformatics, computer science, computational biology, or a related area equivalent to a Danish two-year master's degree. Required skills include strong Python programming, Linux/Unix command-line and shell scripting experience, solid understanding of algorithms and data analysis, knowledge of machine learning theory and implementation, familiarity with basic RNA structure algorithms and programs, excellent written and spoken English, and strong teamwork and communication skills. Desirable experience includes RNA biology, RNA sequence or structure, RNA-protein interactions, machine learning or deep learning, high-throughput sequencing, transcriptomics, CLiP or other omics data analysis, and developing computational methods or predictive models.

How to apply

Apply online in English via the university application portal. Include a motivation letter addressing each essential and desirable requirement, CV, master diploma and transcript (or recent transcript/statement if not completed), list of publications if any, and personal recommendations or an explanation if unavailable.

More information can be found here

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