Postdoctoral Studies in Computational and Structural RNA Biology (Scholarship) – Karolinska Institutet, Solna

Job Description

Do you want to contribute to top quality medical research?
The Department of Microbiology, Tumor and Cell Biology (MTC) at Karolinska Institutet conducts research and teaching within immunology, infection biology, cell biology and cancer. MTC has about 40 research groups and our key words are multidisciplinary, bridging, national and international collaborations.
Vicente Pelechano's Research Group combines experimental and computational approaches to address fundamental biological questions with medical implications. We develop and apply genome-wide technologies to understand how RNA sequence, structure and regulation shape cellular phenotypes. We are particularly interested in RNA biology and in how subtle variations in gene expression lead to differential cellular responses (http://pelechanolab.com/). You will have the opportunity to work in a highly interdisciplinary and international environment and combine the development of state-of-the art genome-wide approaches with the molecular dissection of fundamental biological problems.
Are you interested in understanding how RNA structure shapes post-transcriptional gene regulation? Would you like to develop computational approaches to uncover how RNA sequence and structure control mRNA fate?
Division
Our laboratory is located at the Science for Life Laboratory division from MTC (SciLifeLab, http://www.scilifelab.se/) in the Karolinska Institute campus. SciLifeLab is equipped with state-of-the-art instrumentation and core facilities. Our division is committed to advancing scientific knowledge and developing cutting- edge technologies in the fields of molecular biology, genomics, and bioinformatics.
Duties
The available postdoctoral position concerns developing and applying computational and experimental approaches to study RNA structure and post-transcriptional gene regulation.
The candidate will focus on understanding how sequence variation in untranslated regions (UTRs) shapes RNA structure and thereby influences mRNA fate, including localisation, stability and translation. The candidate will integrate RNA structure prediction and modelling with genome-wide experimental datasets, using complementary systems in human cells and yeast. A particular focus will be placed on alternative 3′ UTR isoforms and on natural and engineered UTR sequence variation, with the aim of developing structure-aware predictive models of RNA regulation. The candidate will perform original research in computational and RNA biology and acquire the experimental and computational skills necessary for the completion of the project. The candidate is expected to communicate scientific results through scientific publications and presentations at scientific meetings, participate in the general duties of the team, and interact effectively with scientists from diverse backgrounds in a highly interdisciplinary and international environment. The working language is English.

Qualifications

• Postdoctoral scholarships may be established for foreign researchers who pursue their merit in Sweden. A foreign researcher is a person living in another country who comes to Sweden with the intention of only staying in Sweden for all or part of their postdoctoral education at KI. Persons who are resident in Sweden and/or have carried out all or part of their academic education at KI or some other educational institution in Sweden cannot be considered for scholarships. The purpose of scholarships for postdoctoral qualification is to promote internationalization and contribute to research qualification after a doctorate or equivalent.
• A scholarship for carrying out postdoctoral research can be granted for a maximum of two years within a four-year period following the receipt of a doctoral degree or equivalent.
• To be eligible for a postdoctoral scholarship, the person must have obtained a doctorate, or a foreign degree deemed to be equivalent to a doctorate. Applicants who have not completed a doctorate at the end of the application period may also apply, provided that all requirements for a completed degree are met before the (intended) start date of the post-doctoral education.
• The successful applicant should have experience interpreting biological data and a strong interest in interdisciplinary research at the interface of RNA biology, computational biology and RNA structure. Suitable candidates should have a strong research background in computational biology, RNA biology, RNA structure or a related field, together with documented experience in computational analysis of gene regulation. Candidates should have high-quality publications, good knowledge of English (spoken and written), and strong motivation to investigate the molecular mechanisms underlying RNA regulation. In the appointment, special weight will be attached to scientific skills relevant to the project and previous research experience.
• A good understanding of RNA biology and post-transcriptional gene regulation is essential, with particular interest in the relationship between RNA sequence, structure and function. The successful applicant should have experience interpreting biological data, formulating hypotheses and developing approaches to test them. Documented experience with computational analyses and bioinformatics, using languages such as Python and/or R, is necessary. Good interpersonal skills and the ability to work effectively in a team are essential.
• In addition to the aforementioned requirements for the position:
• Experience in RNA structural biology, RNA structure prediction and/or structural bioinformatics.
• Experience with large-scale sequence or functional genomics datasets, particularly in the context of UTRs or post-transcriptional gene regulation.
• A strong interest in interdisciplinary method development, together with novel and creative thinking abilities, is essential.
• Meritorious for the position:
• Experience with machine learning or predictive modelling of biological sequences.
• Experience with RNA structure prediction or structure-guided sequence design.
• Experience integrating computational predictions with experimental biological data.
• Experience developing reproducible computational workflows and managing biological datasets.
• Experience in yeast genetics, genomics or RNA biology would be advantageous.

Additional Information

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