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, [email protected] phone +45 23375667

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 ECTS + 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.
• Relevant work experience
• 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.

You can read more about salary levels in the state sector www.loenoverblik.dk (in Danish).

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

Questions

For further information about the scientific content of the position please contact Professor Jan Gorodkin, email [email protected] or for application procedure and formalities, please contact HR Officer, email [email protected] / www.sund.ku.dk

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

Application procedure

Your online application must be submitted in English by clicking ‘Apply for position’ below. Furthermore, your application must include the following documents/attachments – all in PDF format:

• Motivation letter of application. In this letter you must briefly detail, one by one, how you meet the requirements for each item listed under “Essential experience and skills” and “Desirable experience and skills”.
• CV incl. education, work/research experience, language skills and other skills relevant for the position.
• Master Diploma: Certified copy of original Master of Science diploma and transcript of records in the original language, including an authorized English translation if issued in other language than English or Danish. If not completed, a certified/signed copy of a recent transcript of records or a written statement from the institution or supervisor is accepted. As a prerequisite for a PhD fellowship employment, your master’s degree must be equivalent to a Danish master’s degree. We encourage you to read more in the assessment database: https://ufm.dk/en/education/recognition-and-transparency/find-assessments/assessment-database . Please note that we might ask you to obtain an assessment of your education performed by the Ministry of Higher Education and Science
• List of publications (if any)
• Personal Recommendations. If none, please explain why it has not been possible to obtain.

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.

You find information about the recruitment process at: http://employment.ku.dk/faculty/recruitment-process/

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.