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State/Province: North Carolina [NC]
Country: United States [US]
Position Title: Sr. Computational Biologist - Mathematical Pathway Modeler
Job ID: 3142
*Support gene candidate discovery for plant traits and breeding by developing and applying mathematical models of biological pathways.
*Develop and calibrate differential equation based models representing key plant biological pathways.
*Develop and apply methods to utilize plant pathway models for gene candidate identification.
*Work closely with experimental and computational biologists in research teams to design experiments, modeling analyses, and validation efforts.
*Evaluate and recommend new methodologies for model development, calibration, and application.
Accountabilities: *Keep current with the state-of-the-art in mathematical modeling and parameter estimation methodologies.
*Implement cutting edge algorithms to leverage models and advance research goals.
*Provide leadership on mathematical modeling and its applications.
*Consult with diverse stakeholders on experimental design, model development and utilization.
Knowledge, Skills & Experience:
Critical knowledge: :
*Ph.D. or equivalent experience in Applied Mathematics, Biomathematics, Bioengineering, Chemical Engineering, or a related field, preferably with a focus on biological problems.
*Thorough knowledge of mathematical modeling, differential equations, parameter estimation, and biological applications of models.
*At least three years experience developing and applying mathematical models in a life sciences setting.
*At least one year postdoctoral experience or equivalent is highly preferred.
*Experience working effectively in multi-disciplinary teams.
Critical technical, profesional & personal capabilities:
*Experience developing mathematical models in the biological sciences.
*Experience calibrating mathematical models using experimental data and parameter estimation.
*Experience working computationally with systems of differential equations.
*Proficiency in Matlab. Demonstrated ability to communicate effectively with scientific colleagues.
*Excellent oral and written communication skills for both scientific and non-scientific audiences.
Critical leadership capabilities:
*Ability to influence the way biologists think about the problems they work on.
*Ability to integrate into a highly diverse team comprising multiple disciplines, nationalities, and cultural backgrounds.
Critical Success Factors & Key Challenges: *Establish effective partnerships with experimental and computational biologists working in candidate gene discovery.
*Work productively in a team / matrix environment with geographically dispersed stakeholders.
*Identify and incorporate mathematical modeling methodologies from diverse scientific fields for application in plant lead discovery.
*Drive the application of pathway models for the generation of commercially relevant knowledge.
*All applicants must be eligible to work in the US.
*Infrequent travel, including international travel, may be required.