Postdoctor in computational biology / molecular phylogenetics

Postdoctor in computational biology / molecular phylogenetics

Arbetsbeskrivning

The University of Gothenburg tackles society’s challenges with diverse knowledge. 49 000 students and 6 400 employees make the university a large and inspiring place to work and study. Strong research and attractive study programmes attract scientists and students from around the world. With new knowledge and new perspectives, the University contributes to a better future.

At the Department of Biological and Environmental Sciences we have teaching and research activities that stretch from the alpine ecosystem, through forests, cultivated land and streams, all the way into the marine environment. In these environments we study different levels of biological organisation from genes, individuals and populations, to communities and ecosystems. We work within ecology, evolution, physiology, systematics and combinations of these fields in order to understand the impact of natural and anthropogenic changes of the environment.

The Department of Biological and Environmental Sciences is the host of the Gothenburg Global Biodiversity Centre. The Centre has two main goals: to further develop biodiversity research, and to bridge the gap between scientists, the public and industry. The working language is English.

The department is placed at three different localities: in Gothenburg Botanical garden, at Medicinarberget in Gothenburg, and at the marine research station-Kristineberg. The current position is placed at Gothenburg Botanical garden with flexibility for spending time between Stockholm (Swedish Museum of Natural History and the Royal Institute of Technology) and London (Royal Botanic Gardens, Kew). Whenever possible, international collaborations will be carried out through video-conferencing to reduce environmental impact.

 

Project description

The rapid increase in publicly available DNA sequence data now offers exciting opportunities for building the ‘Tree of Life’ (phylogenies) that establishes the relationships and temporal origins of all living organisms. Although several attempts are being made to build comprehensive molecular phylogenies, a major challenge remains in how to effectively add newly generated sequences to such trees without the need to start from scratch every time.

This project – “Online phylogenetics” – will explore emerging Sequential Monte Carlo techniques to add new sequences to existing trees under a fully Bayesian framework. It will then validate the method by building a continuously updating phylogenetic tree for all plant species sequenced to date. Alternative approaches for building large trees, which integrate genomic-wide and single-gene data, may be explored if necessary.

The project is a collaboration among internationally leading researchers at the University of Gothenburg (Gothenburg Global Biodiversity Centre), the Royal Botanic Gardens, Kew, the Swedish Museum of Natural History, the University of Stockholm, the Royal Institute of Technology, Aarhus University and the University of Michigan. Funding is provided through a competitive grant from the Swedish Research Council.

 

Job assignments

This employment includes the following tasks: further development and/or testing of software for phylogenetic analysis; responsibility for managing own workload; production of scientific articles; effective communication across the team and beyond; among other assignments depending on the candidate’s skills and interests in relation to the project’s objectives.  

 

Eligibility

The applicant must hold a PhD degree in an area relevant for the tasks at hand (e.g., computational biology, molecular phylogenetics, bioinformatics) or a foreign exam substantially equivalent to a PhD degree in a relevant subject. Preference will be given to candidates who have been awarded the degree no more than three years before the application deadline. Applicants with a degree awarded earlier may also be preferred if specific reasons exist. Such specific reasons may be a leave due to illness, parental leave or other similar circumstances.



Assessments

We are seeking a highly motivated person to take a leading role in this project. At least one of the following skills are crucial for this employment:


• Experience handling DNA data for molecular phylogenetics, genomics or related fields
• Experience with Bayesian inference
• Basic knowledge in biological systematics, taxonomy and/or molecular dating

What is advantageous/ beneficial:


• Experience with advanced inference algorithms, such as Markov chain Monte Carlo or Sequential Monte Carlo
• Skills in functional or probabilistic programming languages

In addition, the candidate should have published or submitted articles or other scientific deliverables (such as software) in this field, and excellent communication skills in English, written and spoken.

 

The employment

The employment is a full-time position for two years placed at the Department of Biological and Environmental Science.

 

How to apply and for further information 

In order to apply for a position at the University of Gothenburg, you have to register an account in our online recruitment system https://web103.reachmee.com/ext/I005/1035/main?site=7&validator=9b89bead79bb7258ad55c8d75228e5b7〈=UK&rmpage=job&rmjob=17282. It is the responsibility of the applicant to ensure that the application is complete in accordance with the instructions in the job advertisement, and that it is submitted before the deadline. The selection of candidates is made on the basis of the qualifications registered in the application. 

 


In connection to this recruitment, we have already decided which recruitment channels we should use. We therefore decline further contact with vendors, recruitment and staffing companies.

Sammanfattning

  • Arbetsplats: Göteborgs universitet
  • 1 plats
  • 6 månader eller längre
  • Heltid
  • Fast månads- vecko- eller timlön
  • Publicerat: 7 oktober 2020
  • Ansök senast: 10 november 2020

Postadress

Universitetsplatsen 1
Göteborg, 40530

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