Job:(another) Fully-funded PhD scholarship on functional and evolutionary genomics [Apply by 8/15]
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2.8 years ago
Mari ▴ 30

The PhD project will focus on the estimation of the effects of structural variants on various phenotypes bioinformatically and reveal the adaptive evolution of structural variants of farmed salmon under domestication compared to their wild counterparts.

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The successful applicant must meet the conditions defined for admission to a PhD programme at NMBU. The applicant must have an academically relevant education corresponding to a five-year Norwegian degree programme, where 120 credits are at master's degree level. The applicant must have a documented strong academic background in genomics and be able to document proficiency in both written and oral English. For more detailed information on the admission criteria please see the PhD Regulations and the relevant PhD programme description. The applicant must document expertise and interest in the research subject.

Required Academic qualifications

  • Master’s degree in genomics, bioinformatics, evolutionary genetics, or a similar field (120 credits).
  • Experience with large genome data analysis
  • Experience with command-line-based operation of the High-Performance Computing (HPC) system
  • Experience/familiarity with R, Python, and other programming languages
  • Statistical/population genomics knowledge (For example, PLINK, VCFTools, GCTA)

The following experiences and skills will be emphasized:

Experience with RNA-sequencing, or eQTL, GWAS or similar functional genomics analysis (For example, DeSeq2, Kallisto, STAR)

You need to:

  • Have good collaborative skills and high motivation. You will closely work with another PhD student.
  • Work with initiative and creative views.
  • Have analytical and academic approach to research questions.
  • Be proficient in English, both written and spoken.
  • Fish genomics expertise and Norwegian language skill are NOT necessarily required at the time of application.
evolution genomics statistical transcriptome • 704 views
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