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Postdoctoral Fellow on development of multivariate statistical models to predict new phenotypes in dairy cattle 957661

Center for Quantitative Genetics and Genomics (QGG), at the Department of Molecular Biology and Genetics, Aarhus University, is seeking a creative, motivated and productive Postdoctoral Fellow to conduct research on development of multivariate statistical models to predict novel phenotypes in dairy cattle.  Starting date is expected to be as soon as possible.

There is funding for 2 year of employment. In case further external funding is procured within the academic area the candidate is estimated obviously qualified for, an extension can be possible for up to a total maximum of 4 years of employment as a postdoc. 

Research project
In dairy cattle breeding, new phenotypes like energy balance, feed intake, methane emission, sensory data and infra-red spectra data are needed to further improve the genetic potential and management of the dairy cattle population. An important issue regarding many of these new phenotypes is how to measure them in large dairy cattle populations as they often are difficult and expensive to measure. The use of e.g. infra-red spectra from milk samples as a predictor for new phenotypes has the potential to solve this problem. Within the REFFICO project we collect milk IR spectra data on a national scale in addition to large scale genotyping. New phenotypes related to energy balance, feed intake, feed efficiency, and sensory data are measured on all genotyped animals. Currently most phenotypic prediction models based on infra-red spectra are based on partial least squares methodology, but in REFFICO we will develop and implement alternative models to improve the predictions of new phenotypes. Such methods will be based on likelihood or Bayesian methodology.

The candidate will develop and validate models that utilize multivariate infra-red spectral data to predict for new phenotypes in relation to the energy balance, feed intake or feed efficiency of a cow during lactation. In the second part of the project, these new infra-red based prediction models will be applied in the Danish dairy cattle population in order to make a genetic evaluation of the new phenotypes.

Qualifications and competences
• PhD or equivalent in statistics, quantitative genetics, statistical genetics, or related fields
• Documented experience in multivariate statistics, prediction modelling
• Preferably experience in high performance computing including scripting and/or programming in e.g. R/Matlab and C
• Strong skills in oral and written communication in English 
• Documented strong publication record
• Ability to work in a large and diverse group of researchers, and collaborate with both national and international research partners as well as commercial partners

About us
Center for Quantitative Genetics and Genomics (QGG), is a major center for research and education in quantitative genetics, quantitative genomics, and breeding. QGG has large experience in development and implementation of methods for genetic studies and software that is routinely used by several Danish and international research groups and commercial breeding companies. It comprises 20 senior staff and a large group of PhDs and postdocs. The center is part of the Department for Molecular Biology and Genetics and is located at the AU Foulum campus (for the locations of the department see QGG provides a very dynamic and internationally orientated environment with strong collaborations with relevant industrial partners and with several other leading international research groups in the area.
Place of Work and area of Employment
The place of work is Blichers Allé 20, DK-8830 Tjele, and the area of employment is Aarhus University with related departments.

For further information, please contact associate professor Bart Buitenhuis;

Application procedure
Shortlisting is used. This means that after the deadline for applications and with the assistance from the assessment committee chairman, and the appointment committee if necessary, the head of department selects the candidates to be evaluated. All applicants will be notified whether or not their applications have been sent to an expert assessment committee for evaluation. The selected applicants will be informed about the composition of the committee, and each applicant is given the opportunity to comment on the part of the assessment that concerns him/her self. Once the recruitment process is completed a final letter of rejection is sent to the deselected applicants, including the main considerations emphasized during the selection process.

Formalities and salary range

Science and Technology refers to the Ministerial Order on the Appointment of Academic Staff at Danish Universities under the Danish Ministry of Science, Technology and Innovation.

The application must be in English and include a curriculum vitae, degree certificate, a complete list of publications, a statement of future research plans and information about research activities, teaching portfolio and verified information on previous teaching experience (if any). Guidelines for applicants can be found here.

Appointment shall be in accordance with the collective labour agreement between the Danish Ministry of Finance and the Danish Confederation of Professional Associations. Further information on qualification requirements and job content may be found in the Memorandum on Job Structure for Academic Staff at Danish Universities. Salary depends on seniority as agreed between the Danish Ministry of Finance and the Confederation of Professional Associations.

All interested candidates are encouraged to apply, regardless of their personal background. Research activities will be evaluated in relation to actual research time. Thus, we encourage applicants to specify periods of leave without research activities, in order to be able to subtract these periods from the span of the scientific career during the evaluation of scientific productivity.

Aarhus University offers Relocation service to International researchers. You can read more about it here.


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