Researcher Postdoc
- Employer
- Cornell University
- Location
- Cornell University, Ithaca, New York
- Salary
- Salary commensurate with experience.
- Closing date
- Feb 28, 2021
View more
- Discipline
- Life Sciences, Bioinformatics, Biotechnology, Botany/Plant Science, Computational Biology, Genomics
- Position Type
- Full Time
- Job Type
- Postdoc
- Organization Type
- Academia
Researcher Postdoc
Leading quantitative genetics lab at Cornell University is hiring a postdoc level scientist focused on our research. We are looking for strong skills in bioinformatics and an interest in connecting basic science with applied plant breeding to adapt to and combat climate change.
Join Ed Buckler and his group at Cornell University and help develop models based in genomics, molecular biology, and large-scale field evaluations to understand field performance and adaptation. We have a history of bridging quantitative genetics and genomics and applying this knowledge to improving crops with the aim of reducing hunger and environmental impact. Crop genomics is at a key moment, where the technologies to design crops (genomic selection and genome editing) have never been more powerful. However, to effectively apply these technologies, we must first improve our capacity to integrate functional variants into their regulatory and physiological networks. We are looking for researchers wanting to tackle these important problems of modeling chromatin, expression, translation, protein-protein interactions, and enzyme activity in order to connect these molecular changes to a wide range of phenotypes.
The postdoc should have a background in machine learning, bioinformatics of genomic and molecular data, quantitative genetics, and/or statistical genetics. Strong skills in computer programming and modeling are necessary. Researchers with experience in human, animal, and other model organisms and evolution are especially encouraged to apply.
The successful candidate will assist in building tools to develop plant regulatory networks that leverage data from models such as Arabidopsis, yeast, and Chlamydomonas, and apply the networks initially to the quantitative genetics of maize, sorghum, and cassava. Longer term these networks will be tested in hundreds of related wild species.
Interested candidates should submit a cover letter and CV to Sara Miller at sara.miller@cornell.edu.
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