A PhD Research Fellowship in Population Genomics/genetics is available at the Centre for Ecological and Evolutionary Synthesis (CEES), Department of Biosciences,
The fellowship will be for a period of 3 years, with no compulsory work. Starting date from 01.01.2016 and no later than 01.03.2016.
No one can be appointed for more than one fixed-term period at the same institution.
Job description:
The successful candidate will work within the project “MARine MAnagement and Ecosystem Dynamics under climate change (MARmaED)” (www.marmaed.eu) an Innovative Training Network funded by the Marie Skłodowska-Curie Action (The European Union's Horizon 2020) under grant agreement No 675997 for the period 2015-2019. MARmaED is an international and interdisciplinary network that unifies specific and complementary competences in marine sciences from Norway, Finland, Denmark, the Netherlands, Germany and France to investigate how the cumulative stress from biodiversity loss, climate change and harvesting will affect Europe’s complex marine systems and the consequences for optimal resource management. The project’s main aim is to investigate how combined anthropogenic and climatic changes affect different harvested ecosystems (terrestrial, freshwater, and marine – particularly, but not only, in Arctic regions) and how management strategies can be improved to ensure sustainable exploitation and resilience. MARmaED will provide salary for 15 PhD projects.
Genetic structure of the Northeast arctic cod: impact of climate change?
Within this sub-project the PhD-candidate will work interdisciplinary – with the overarching goal to implement and use genomic data into population dynamic models – and study how adaptation to the environment shapes the spatiotemporal dispersal and genetic connectivity of the Atlantic cod. To reach this goal the candidate will use ancient DNA (aDNA) methodology to create whole genome data from historical samples using high-throughput sequencing. The long-term genomic perspective generated by these data will be used as a basis for advanced statistical modelling aimed to infer detailed knowledge on the spatiotemporal connectivity of Atlantic cod populations. This PhD-project will be tightly linked to an already ongoing project – the Aqua Genome project (http://www.aquagenome.uio.no) – where one of the major undertakings is to sequence 1000 Atlantic cod genomes from a variety of locations and populations. The study will derive fundamental biological knowledge with broad management implications, for instance aiding the development of optimal management strategies and sustainable fisheries.
Requirements:
The Faculty of Mathematics and Natural Sciences has a strategic ambition of being a leading research faculty. Candidates for these fellowships will be selected in accordance with this, and expected to be in the upper segment of their class with respect to academic credentials.
Applicants must hold a master-degree or equivalent, or must have submitted his/her master's thesis for assessment prior to the application deadline within population genomics/genetics and or ecology. It is a condition of employment that the master's degree has been awarded. Documented expertise within either population genomics/genetics is required. Further, experience with the generation and bioinformatic analyses of genomic datasets will be an asset. An additional background and/or strong interest in statistical modelling, demographic and spatial modelling and/or quantitative population modelling will be a distinct advantage.
The candidate must fulfil the requirement of eligibility dictate by EU; being resident in the host country not more than 12 months all in all during the last 36 months from the start of the PhD project. In addition, the candidate cannot have a longer than 4 years research experience.
We seek a highly motivated, enthusiastic person with the ambition to gain insight and publish papers in leading, international journals, and in possession of strong interpersonal skills and willingness to work in close collaboration with others.
The purpose of the fellowship is research training leading to the successful completion of a PhD degree.
The fellowship requires admission to the PhD programme at the Faculty of Mathematics and Natural Sciences. The application to the PhD programme must be submitted to the department no later than two months after taking up the position. For more information see:
http://www.uio.no/english/research/doctoral-degree-and-career/phd/application/
http://www.mn.uio.no/english/research/doctoral-degree-and-career/phd-programme/index.html
A good command of English is required.
http://www.mn.uio.no/english/research/doctoral-degree-and-career/regulations/proficiency-requirements.html
Salary:
Position code 1017, Pay grade: 50 - 57 (NOK 430 500– 492 700 per year)
The application must include:
- Application letter including a statement of interest, briefly summarizing your scientific work and interests and describing how you fit the description of the person we seek
- CV (summarizing education, positions, pedagogical experience, administrative experience and other qualifying activity)
- Copies of educational certificates, transcript of records and letters of recommendation
- Documentation of English proficiencyhttp://www.mn.uio.no/english/research/doctoral-degree-and-career/regulations/proficiency-requirements.html
- If applies, a complete list of publications and unpublished works, and up to 5 academic work that applicant wishes to be considered by the evaluation committee
- Names and contact details of 2-3 references (name, relation to candidate, e-mail and telephone number)
Foreign applicants are advised to attach an explanation of their University's grading system.
Please remember that all documents should be in English or a Scandinavian language.
In accordance with the University of Oslo's equal opportunities policy, we invite applications from all interested individuals regardless of gender or ethnicity.
UiO has an agreement for all employees, aiming to secure rights to research results a.o.
This opportunity has expired. It was originally published here:
http://uio.easycruit.com/vacancy/1523323/96871?iso=no