Intern – Computational Biology & Genetics

Posted on by Micaela Brun
Job ID:
Job date: 2018-03-02
End Date:

Company : Biogen 

Country :

Role : Student 


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Job Description:
This internship assignment is with Biogen’s Statistical Genetics & Genetic Epidemiology team, focused on multiple sclerosis (MS). The team is under the Computational Biology & Genomics team and primarily supports Biogen’s Research & Early Development function to identify and prioritize drug targets, as well as identify genetic markers for patient stratification. This assignment will focus on conducting genetic studies of MS in our clinical trial data.

Through this internship, the student will have the opportunity to learn a wide variety of human genetics software and analysis techniques, including:

  • Conducting human leukocyte antigen (HLA) and genome-wide association studies for continuous and binary phenotypes in multiple sclerosis cases (linear and logistic regression using R or PLINK software)
  • Meta-analysis
  • Creating and testing genetic risk scores based on common genetic variation in multiple sclerosis patients and healthy controls
  • Mendelian randomization analysis
Qualifications:

To participate in the Biogen Internship Program, students must meet the following eligibility criteria:

  • Legal authorization to work in the U.S.
  • Enrollment in a full-time undergraduate or graduate program, returning to the academic program following Biogen internship assignment
  • Minimum grade point average of 3.2 preferred
  • At least 18 years of age prior to the scheduled start date
  • Completed at least one year of undergraduate studies
Required for this internship:
  • Experience with statistical software (e.g. R, SAS or MATLAB)
  • Programming / scripting skills (e.g. Perl, Python, UNIX Shell or Java)
  • Outstanding communication & teamwork skills
  • Available for full-time employment from June to August
Preferred qualifications:
  • Experience with Mendelian randomization analysis and genetic risk scores
  • Experienced analyzing human genetic data (DNA) & testing for association with complex disease
  • Experience with statistical genetics software (e.g. PLINK)
  • Experience using large-scale genetic data from academic collaborations, public-private partnerships and/or clinical trials
  • Experience with linear regression and logistic regression analysis
  • Experience with classical human leukocyte antigen (HLA) allele imputation software (e.g. HIBAG, SNP2HLA or HLA*IMP)
  • Experience with genome-wide SNP genotype imputation (e.g. IMPUTE, MACH or BEAGLE)
  • Experience with principal components analysis (e.g. Eigensoft)
Education:

Current graduate student in statistical genetics, genetic epidemiology, human genetics, biostatistics, computational biology, computational genetics, computer science or bioinformatics.

PhD student preferred.

Skills :

Areas :

Additional Info:
Employment Category: Full-Time Regular

Experience Level :Internship or Co-op

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