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Havforskningsinstituttet


Address: Nordnesgaten 50, 5005 BERGEN
Phone: +47 55238500
Web: http://www.imr.no/en
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Vacancy Details

Created 22.02.2017
Expires 26.03.2017
Company Havforskningsinstituttet
Employment Full-time
Job type Temporary
County Hordaland
Phone +47 55238500
Fax
Email post@imr.no
WWW http://www.imr.no/en

Postdoc. fellow in fish population modelling for Mng.ment Strategy Evaluation

 

The Institute of Marine Research (IMR) in Norway has an immediate opening for a 4-year position as postdoctoral fellow in the research group for Demersal Fish.

 

The post-doc research will be conducted within a multidisciplinary project at IMR that aims to quantify and reduce uncertainty in stock assessments (REDUS). Through REDUS we aim to develop and implement a generic framework for analysis, estimation and uncertainty evaluation that will support more optimal fisheries management advice and better prioritization of fisheries monitoring and research. The cross disciplinary project team will include 3-4 post-docs.

 

The Demersal fish group works on research, monitoring and advice on demersal fish species, using biological, statistical and computer models. The group works in close collaboration with other research groups at the IMR and contributes to associated research fields including impacts of climate change, ecology, integrated ecosystem-based management to name a few. Extensive research collaboration with national and international institutions is expected and encouraged.

 

The principal areas of research for the current postdoc position in population modeling will be in development of the Management Strategy Evaluation tool, working with a dedicated programmer to link together a set of different models with varying complexity, and in developing and analyzing case studies to test the tool. Research topics will include developing the linkage between models, developing and analyzing management strategies, and analyzing the relative importance of different sources of uncertainty (data noise, bias, structural errors, model choice).

 

Qualifications

 

Candidates must have completed a PhD or equivalent degree involving modeling, for example via applied mathematics, applied statistics, fish population modeling, ecological modeling or a related quantitative field. Experience of fisheries modeling, and especially Management Strategy Evaluations, is an advantage but not a requirement.

The successful candidate should have strong quantitative skills and experience in programming in R. Experience in an additional programming language (for example C++) would be an advantage. Good oral and written communication skills in English are required. A working knowledge of the Norwegian language is not required, but language training courses in Norwegian will be offered. The ability to work in a multi-disciplinary team setting is necessary.

 

We offer:

 

  • A positive, challenging and creative work environment.
  • The opportunity to work in a national institute with a high level of international contact.
  • Flexible working hours, and a wide range of welfare services.

The Institute offersa governmentally regulated salary as 1352 postdoctoral fellow and an excellent pension scheme through the Norwegian Public Service Pension Funds, and other welfare benefits (see www.spk.no/en/ for more information).

The work place will be at IMR in Bergen.

 

Additional information

 

If you need more information, please contact Dr. Daniel Howell (e-mail: daniel.howell@imr.no or +47 920 63 885) or research group leader Erik Olsen (e-mail: eriko@imr.no, phone: +47 934 39 256). You can also visit our web site at www.imr.no.

IMR is an "Including Working Life Enterprise" concerned with diversity and therefore encourages all qualified candidates to apply. Please note that information about applicants may be made public even if an applicant has requested to be exempted from the list of applicants. Applicants will be notified about this in advance.

Please apply electronically using the link on this page, attaching a short letter of motivation, the names and contact details of at least two references, your CV with documentation to support your application (including a list of publications, transcripts or other documentation, and a selection of your most relevant publications).