Postdoctoral Fellow

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The Gragert Lab in the Tulane Deming Department of Medicine, Section of Biomedical Informatics and Genomics, is seeking a Postdoctoral Fellow with a computational research background in bioinformatics, immunogenetics, and/or transplantation.

 

The Gragert Lab focuses on investigating the role of immune gene variation (HLA and KIR) in transplantation, cancer, and immune-mediated diseases. The role of this postdoctoral researcher will be to develop software and bioinformatics workflows for analysis of immunogenetic data, conduct genetic association studies, and build population genetic models. This position will specifically involve analyzing HLA immunogenetics and antibody data in the context of solid organ allocation and transplant outcomes and other projects as assigned by the principal investigator Dr. Loren Gragert. The postdoc fellow will also be responsible for developing manuscripts/presentations as well as mentoring other lab trainees as needed.

 

See the Gragert laboratory website for more information on lab activities: http://hla.tulane.edu

 

Required Applicant Materials:

Interested candidates should submit the following materials:

• Curriculum Vitae
• Contact information for at least three professional references

 

For further inquiries about this position, please email Dr. Loren Gragert, at lgragert@tulane.edu. 

 

• Execute biomedical research as assigned by the laboratory Principal Investigator.

• Follows experimental design in a careful and timely manner

   

• Maintain an accurate and up to date written record of all experiments and protocols.

   

• Translate research data into publication quality figures and tables.

• Assist in the care and management of laboratory equipment and facilities and other duties delegated by the Principal Investigator. 

• PhD in Genetics, Immunology, Bioinformatics, Computer Science, Statistics, Mathematics, or a related science and engineering field.

• Experience with bioinformatics analysis of DNA sequence data.

• Computer programming experience in a statistical programming language such as R and a scripting language such as Python.

   

  Experience with biological data science including managing and analyzing genetics data and applying statistical methods.

• Expertise in machine learning and/or development of novel statistical methods.