PhD position in RNA structure computational analysis neural sublocalization of transcripts

KU; København; Hybrid; DKK 323,000 - 387,000; Full time

Job summary

The University of Copenhagen welcomes applications for a PhD position in the Gorodkin lab, within the Section for Health Data Science and AI, Department of Public Health. The project builds a predictive framework for subcellular RNA localization in neurons, integrating sequence, structure and RBP data to understand healthy and diseased states.

The PhD program is a 3-year fixed-term research education; the start date is February 1, 2027. Salary follows the Danish PhD pay scale with pension.

Qualifications

• MSc in bioinformatics, computational biology or related field (two-year Danish master’s equivalent).
• Strong Python programming experience and Linux/Unix proficiency.
• Excellent written and spoken English; collaborative team player.

Responsibilities

• Develop and evaluate models to predict neuronal RNA localization.
• Integrate RNA sequence, structure and RBP interaction data.
• Collaborate across computational and experimental teams; disseminate findings.

Skills

Python

Linux/Unix

Shell scripting

Algorithms

Machine learning

English proficiency

Team collaboration

Education

MSc in bioinformatics/computational biology

Tools

Python

Linux/Unix

Job description

PhD position in RNA structure computational analysis neural sublocalization of transcripts

We have a PhD position available in the Gorodkin lab at the Section for Health Data Science and AI at the Department of Public Health, Faculty of Health and Medical Sciences at University of Copenhagen.

The project concerns the development of a predictive computational framework for understanding the subcellular localization of polyadenylated RNAs in neurons, including mRNAs and long noncoding RNAs. The project will integrate RNA sequence, structure, RNA-binding protein interactions, and biological function to uncover the rules governing RNA localization in healthy, degenerating, and regenerating neurons.

Start date is February 1, 2027.

Principal supervisor is Professor Jan Gorodkin, Department of Public Health, [e-mail] phone [phone]

The project

The project aims to develop a predictive computational framework for neuronal RNA localization by combining RNA sequence and structure information with RNA-binding protein (RBP) interactions and biological function. The framework will use data on endogenous and designed RNAs in healthy, degenerating, and regenerating neurons.

The project will integrate existing datasets on neuronal RNA localization, including Frac-seq and N-zip data, with RNA structure and RBP-binding information. Computational approaches will include feature-based classifiers and machine/deep learning methods, including sequence models such as convolutional neural networks and transformers.

You will help develop and evaluate models that predict whether RNAs localize to neuronal cell bodies or neurites, combine complementary experimental datasets, and identify sequence and structural features that contribute to localization. The work will also explore how RNA localization changes in neurodegeneration and regeneration, with a focus on disease-relevant models such as amyotrophic lateral sclerosis (ALS).

Your key tasks as a PhD student at SUND are:

• Carrying through an independent research project under supervision.
• Completing PhD courses or other equivalent education corresponding to approximately 30 ECTS points.
• Participating in active research environments including a stay at another research team.
• Obtaining experience with teaching or other types of dissemination related to your PhD project
• Teaching and disseminating your knowledge.
• Writing a PhD thesis on the grounds of your project

PhD Programme Description: The PhD programme is a three-year full-time research education within the framework of the 5+3 scheme, intended for candidates holding a relevant academic degree within the project’s subject area.

Qualifications: If you have completed your academic education in Denmark, the admission to the PhD programme requires a relevant Master’s degree (equivalent to 180 ECTS BSc + 120 ECTS MSc).

• If you have an academic education from abroad, you must have either a degree equivalent to a Danish master's degree (180 ETCS + 120 ECTS MSc), or at a minimum, a bachelor’s degree equivalent to a Danish bachelor's degree (180 ECTS) and be academically qualified at master's level.
• As part of the assessment of whether you meet the educational requirements, you must also achieve a positive academic evaluation and be assessed as the best qualified for the position.

Who are we looking for

We are looking for a highly motivated candidate with a strong computational background and an interest in RNA biology and neuroscience. You will contribute to the development of computational methods for predicting neuronal RNA localization by integrating RNA sequence, RNA structure, and RNA-binding protein interactions. You will work in a cross-disciplinary and international research environment and collaborate closely with researchers working on computational and experimental aspects of the project. We value curiosity, independence, clear communication, and the ability to work constructively as part of a team.

Essential experience and skills:

• You have completed an MSc degree in bioinformatics, computer science, computational biology, or a related area. Please note that your master’s degree must be equivalent to a Danish master’s degree (two years)
• You are highly experienced in Python
• You have strong experience working in a Linux/Unix environment, including command-line tools and shell scripting
• You have a solid understanding of algorithms and data analysis, and knowledge of machine learning including theory and practical implementation
• You are well familiar basic RNA structure algorithms and programs
• You have excellent written and spoken English skills
• You communicate well and are a strong collaborative team player

Desirable experience and skills:

• Strong knowledge and experience working with RNA biology, RNA sequence or structure, or RNA–protein interactions
• Substantial experience with machine learning or deep learning methods
• Experience with high-throughput sequencing, transcriptomics, CLiP or other omics data analysis
• Experience developing computational methods or predictive models

Key selection criteria:

• Professional qualifications relevant for the position.
• Fluency in English

Our research group Our research group Computational Biology and Bioinformatics work with computational algorithms and methods for molecular structure and interactions. We have excellent computational infrastructure and further access to supercomputing when needed. The research group is working on a range of bioinformatical aspects both algorithm, data and omics-wise. The research group is currently located on Frederiksberg Campus but will move physically to the Department of Public Health at City Campus at the Municipal Hospital on Øster Farimagsgade. Our research environment is highly international and stimulating. We frequently organize seminars, workshops, summer schools with international speakers and have retreats with our international collaborators.

Terms of employment The average weekly working hours are 37 hours per week.

The position is a fixed-term position limited to a period of 3 years as PhD-student. The starting date is February 1, 2027.

The employment is conditioned upon the applicant’s successful enrolment as a PhD student at the Graduate School at the Faculty of Health and Medical Sciences, University of Copenhagen. This requires submission and acceptance of an application for the specific project formulated by the applicant.

The PhD study must be completed in accordance with The Ministerial Order on the PhD programme (2013) and the Faculty’s rules on achieving the degree.

Salary, pension and terms of employment are in accordance with the agreement between the Ministry of Taxation and The Danish Confederation of Professional Associations on Academics in the State. Depending on seniority, the monthly salary starts at approximately 31,850 DKK/Roughly 4,260 EUR (August 2026 level) plus pension.

The position is covered by the Job Structure for Academic Staff at Universities 2025.

Foreign applicants may find this link useful: www.ism.ku.dk (International Staff Mobility).

Deadline for applications: 4 november 2026, 23.59pm CET

We reserve the right not to consider material received after the deadline, and not to consider applications that do not live up to the abovementioned requirements.

The further process After the expiry of the deadline for applications, the authorized recruitment manager selects applicants for assessment on the advice of the hiring committee. All applicants are then immediately notified whether their application has been passed for assessment by an unbiased assessor.

The assessor makes a non-prioritized assessment of the academic qualifications and experience with respect to the above-mentioned area of research, techniques, skills and other requirements listed in the advertisement.

Once the assessment work has been completed each applicant has the opportunity to comment on the part of the assessment that relates to the applicant him/herself.

The applicants will be assessed according to the Ministerial Order no. 242 of 13 March 2012 on the Appointment of Academic Staff at Universities.

The University of Copenhagen wish to reflect the diversity of society and encourage all qualified candidates to apply regardless of personal background.

Part of the InternationalAllianceof Research Universities (IARU), and among Europe’s top-ranking universities, the University of Copenhagen promotes research and teaching of the highest international standard. Rich in tradition and modern in outlook, the University gives students and staff the opportunity to cultivate their talent in an ambitious and informal environment. An effective organisation – with good working conditions and a collaborative work culture – creates the ideal framework for a successful academic career.

Department/Location: Department of Public Health