Archived Post

From  Sat Jun  8 22:29:39 2019
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From: "Gondro, Cedric" <> 
Postmaster: submission approved by list moderator
To: Members of AnGenMap <>
Subject: Research Associate – Artificial Intelligence and Statistical
        Genetics at Michigan State University
Date: Sat, 08 Jun 2019 22:29:39 -0500

Hello All,

We have an opening for a postdoc within the Quantitative Genetics group at
MSU to work on AI methods for genomic prediction.

Please distribute to potential candidates.

Cheers, Cedric

Research Associate – Artificial Intelligence and Statistical Genetics at
Michigan State University

The Animal Quantitative Genetics group at Michigan State University is
seeking a postdoctoral research associate for a 3-year postdoctoral
research associate position in the area of Artificial Intelligence and
Statistical Genetics to work with the Department of Computer Science and
Engineering and the Animal Quantitative Genetics group at Michigan State
University. The successful candidate is expected to independently develop
AI methodology applied to genomic prediction and further knowledge in this
research area, including novel methods for genomic prediction and genomic

The position is for a period of three years conditional on yearly
performance review, with possibility of further appointment subject to
funding. Applicants must have completed a PhD degree in Artificial
Intelligence, bioinformatics, statistical genetics, animal genetics or a
related area. They should demonstrate high research productivity,
proficiency in computer programming, particularly C++ and R, a thorough
knowledge of Artificial Intelligence, massively parallel programming
paradigms and the use of high-performance libraries in HPC environments.
Applicants should possess excellent skills in analytical and creative
thinking. Specific and relevant experience in the research area is highly
desirable, particularly genomic prediction. The specific duties of this
position include:

* Develop and test new methods for genomic prediction, primarily using
  Artificial Intelligence methodology.
* Develop methods to make use of biological knowledge for genomic
* Develop and apply methods and software for effective use of sequence data
  in genomic prediction.
* Report on results in peer reviewed journal papers.
* Write grant proposals in the area.
* Assist with some undergraduate and graduate teaching, provide assistance
  with supervision of graduate students

Selection Criteria

 1. Appropriate qualifications and research training relevant to the duties,
    including completion of a PhD degree artificial intelligence, statistical
    genetics, bioinformatics or animal genetics.
 2. Experience with Artificial Intelligence methods and parallel programming
 3. Strong coding skills with high-performance libraries
 4. Experience in computer programming, particularly C++ and R. Programming
    for mobile platforms and GPUs is a plus.
 5. A strong record of research achievement and publication, relative to
 6. Ability to communicate research outcomes and research ideas
 7. Some work experience in the relevant field of study
 8. Some experience in working with public databases (NCBI, EMBL…)
 9. The ability to take initiatives and independently develop research proposals
10. Conceptual understanding of quantitative genetics and its role in animal
     breeding programs.

Questions about the position should be directed to Prof. Cedric Gondro
(, Department of Animal Science, MSU or Prof Wolfgang
Banzhaf (, Department of Computer Science and
Engineering, MSU. Interested candidates need to apply online and submit a
letter explaining their background and career plans, accompanied by a C.V.
and a description of relevant experience.

The position is initially available for three years subject to satisfactory
annual review. The appointment can be further extended subject to
availability of funding. Salary is competitive and based on career stage,
medical benefits are offered in the salary package. Travel and training
opportunities will be provided to the successful candidate. Apply online

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