Job Description:
UCLA has established the interdepartmental Institute for Quantitative and Computational Biosciences (QCBio) to lead the transformation of biology and biomedicine into a data-rich and math-based, truly predictive science. QCBio faculty pioneer novel measurement capabilities, leverage electronic databases, and develop diverse computational approaches to accelerate (i) discovery across biological scales, (ii) the translation of basic knowledge to application, and (iii) the transformation of biosciences research training and education.
QCBio, housed within Life Sciences of the UCLA College, is partnering with academic departments across the College, the David Geffen School of Medicine and the Henry Samueli School of Engineering and Applied Sciences to recruit six or more faculty over the coming three years, spanning diverse areas of the Quantitative and Computational Biosciences, including
Big Data in Biomedicine & Public Health
Genomics, Proteomics, Metabolomics
Systems Biology & Multi-scale Modeling
Dynamical Regulatory Networks
Stochasticity, Variability, Robustness
Stem Cells & Development
Cancer, Signaling, Metabolism
Infection & Immunity
Microbes & Hosts
Genetics & Epidemiology
Evolutionary Genomics & Modeling
Plants & Ecosystems
We are seeking candidates for any faculty rank with strong biosciences research programs that involve the development and use of novel computational methodologies, and who share a sense of mission in the QCBio revolution of the biosciences.
Applicants should submit a cover letter, curriculum vitae, list of referees, a research statement, a teaching statement, and a diversity statement about activities to promote participation of underrepresented minorities and underserved populations on-line to https://recruit.apo.ucla.edu/apply/JPF00771. Review of applications will begin February 1, 2015.
As a campus with a diverse student body, we encourage applications from women, minorities, and individuals with a history of mentoring under-represented minorities in the sciences. UCLA is an affirmative action/equal opportunity employer with a strong institutional commitment to the achievement of faculty and staff diversity. The University of California is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, age or protected veteran status. For the complete University of California nondiscrimination and affirmative action policy see: UC Nondiscrimination & Affirmative Action Policy (http://policy.ucop.edu/doc/4000376/NondiscrimAffirmAct)
UCLA is California's largest university, with an enrollment of nearly 38,000 undergraduate and graduate students. The UCLA College of Letters and Science and the university's 11 professional schools feature renowned faculty and 323 degree programs and majors. The Biosciences at UCLA include more than 300 faculty members, many top-ten ranked departments, and is consistently in the top ten in NIH funding.
Additional Info:
[Click Here to Access the Original Job Post]
UCLA has established the interdepartmental Institute for Quantitative and Computational Biosciences (QCBio) to lead the transformation of biology and biomedicine into a data-rich and math-based, truly predictive science. QCBio faculty pioneer novel measurement capabilities, leverage electronic databases, and develop diverse computational approaches to accelerate (i) discovery across biological scales, (ii) the translation of basic knowledge to application, and (iii) the transformation of biosciences research training and education.
QCBio, housed within Life Sciences of the UCLA College, is partnering with academic departments across the College, the David Geffen School of Medicine and the Henry Samueli School of Engineering and Applied Sciences to recruit six or more faculty over the coming three years, spanning diverse areas of the Quantitative and Computational Biosciences, including
Big Data in Biomedicine & Public Health
Genomics, Proteomics, Metabolomics
Systems Biology & Multi-scale Modeling
Dynamical Regulatory Networks
Stochasticity, Variability, Robustness
Stem Cells & Development
Cancer, Signaling, Metabolism
Infection & Immunity
Microbes & Hosts
Genetics & Epidemiology
Evolutionary Genomics & Modeling
Plants & Ecosystems
We are seeking candidates for any faculty rank with strong biosciences research programs that involve the development and use of novel computational methodologies, and who share a sense of mission in the QCBio revolution of the biosciences.
Applicants should submit a cover letter, curriculum vitae, list of referees, a research statement, a teaching statement, and a diversity statement about activities to promote participation of underrepresented minorities and underserved populations on-line to https://recruit.apo.ucla.edu/apply/JPF00771. Review of applications will begin February 1, 2015.
As a campus with a diverse student body, we encourage applications from women, minorities, and individuals with a history of mentoring under-represented minorities in the sciences. UCLA is an affirmative action/equal opportunity employer with a strong institutional commitment to the achievement of faculty and staff diversity. The University of California is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, age or protected veteran status. For the complete University of California nondiscrimination and affirmative action policy see: UC Nondiscrimination & Affirmative Action Policy (http://policy.ucop.edu/doc/4000376/NondiscrimAffirmAct)
UCLA is California's largest university, with an enrollment of nearly 38,000 undergraduate and graduate students. The UCLA College of Letters and Science and the university's 11 professional schools feature renowned faculty and 323 degree programs and majors. The Biosciences at UCLA include more than 300 faculty members, many top-ten ranked departments, and is consistently in the top ten in NIH funding.
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Additional Info:
[Click Here to Access the Original Job Post]