Computational Biologist (Postdoctoral position)

The Institute

The research focus of the European Translational Oncology Prevention and Screening (EUTOPS) Institute at the University of Innsbruck is to identify and validate epigenetic signatures for individualised prevention, risk prediction, and early detection of cancer in line with the principles of P4 medicine (predictive, preventive, personalised and participatory). Within this context, our work focuses on DNA methylation-based risk prediction and monitoring of cancer preventive measures in a translational setting, applying high throughput methodologies in international clinical trials and population-based samples. EUTOPS is supported by the Land Tirol and led by Professor Martin Widschwendter, who also holds a professorship at University College London, UK, and a guest professorship at the Karolinska Institutet, Stockholm, Sweden. For more information please visit our website www.eutops.institute

The Role

You will join a small team of bioinformaticians/computational biologists working on a variety of projects in the field of cancer risk prediction and prevention. The post is offered for one year in the first instance.

We highly value team members capable of working independently with a sense of self-initiative and ‘can do’ attitude. Specifically, the role will involve:

• Applying existing and/or newly developed tools for processing of Illumina EPIC array, genome sequencing (including Nanopore sequencing), single cell RNA sequencing, and RT-PCR data.
• Statistical data analysis and interpretation/visualisation of results.
• Developing new methods and workflows for storing, handling and analysing the above data.
• Close collaborations with the wider team including other bioinformaticians/computational biologists and wet lab biologists
• Presentation of research results at national and international conferences and congresses.

Your Profile

Essential requirements:

• Completed PhD in bioinformatics / computational biology / biostatistics or a related quantitative field (e.g. mathematics, statistics, physics) with an interest in biological research issues.
• Experience in managing large molecular/phenotypic datasets.
• Ability to work in R, Shell, and/or BASH
• A proven publication track record.

Any of the following experience would also be desirable:

• Epigenetic and/or genetic data analysis.
• Epidemiological data collection and analysis.
• Github.

All candidates will be asked to demonstrate:

• Excellent interpersonal and communication skills with a commitment to collaboration in research.
• Excellent teamwork and project group interaction and cooperation.
• Excellent organisational and time management skills with the ability to work independently, precisely and prioritise work to meet objectives and tight deadlines.
• Fluent English.

The minimum salary for this position is 4,061EURO/month (14 times). The remuneration offered will increase with relevant professional experience. In addition, the university offers numerous attractive additional benefits (http://www.uibk.ac.at/universitaet/zusatzleistungen/ ).

As part of its personnel policy, the University of Innsbruck attaches great importance to equal opportunities and diversity. The University of Innsbruck strives to increase the proportion of women it employs and therefore expressly invites qualified women to apply. This particularly applies to management roles as well as to scientific positions. In the event of under-representation, priority will be given to women with the same qualifications.

In order to comply with Austrian disability legislation, qualified persons are expressly encouraged to apply. www.uibk.ac.at/karriere

If you are interested in applying for this position, please send your CV and a covering letter to Dr Julie Bennett at Julie.Bennett@uibk.ac.at . For informal enquiries please contact Professor Martin Widschwendter at martin.widschwendter@uibk.ac.at  or Dr Chiara Herzog at Chiara.Herzog@uibk.ac.at . If shortlisted for interview, you will be asked to complete a short data analysis test.