Critical Assessment of Genome Interpretation (CAGI) Lead Scientist
Research Group of Steven Brenner University of California, Berkeley
Establish the state-of-the-art in genome interpretation
We are seeking a leader for the Critical Assessment of Genome Interpretation (CAGI, \'k-j\), a community experiment to evaluate the prediction of phenotypes from genetic variation. CAGI objectively assesses computational methods for predicting the phenotypic impacts of genomic variation. In this experiment, modeled on the Critical Assessment of Structure Prediction (CASP), participants are provided genotypic data and make predictions of resulting molecular, cellular, or organismal phenotype.
These predictions are evaluated against experimental and clinical characterizations, and independent assessors perform the evaluations. Community workshops are held to disseminate results, assess our collective ability to make accurate and meaningful phenotypic predictions, and better understand progress in the field. From this experiment, we identify bottlenecks in genome interpretation, inform critical areas of future research, and connect researchers from diverse disciplines whose expertise is essential to methods for genome interpretation. The fourth CAGI experiment assessed 174 predictions for this year's 11 diverse challenges. These predictions were made by 37 predictor groups who hailed from labs located in 13 different countries. This led to a special issue of Human Mutation with 23 papers. The fifth CAGI experiment is underway.
Responsibilities: The CAGI Lead Scientist will be primarily responsible for operating the CAGI experiment, from developing challenges to managing prediction submissions and assessments to dissemination of results. Each new challenge requires extensive interactions with the data set provider to develop the most informative challenge. Supervision of assessment includes interacting with assessors, developing standard and automated assessment protocols, and ensuring that uniform standards are applied and that proposed assessment methods are appropriate, as well as reviewing assessment results and ensuring that the necessary technical support is provided.
Prediction management includes engaging a broad and diverse community, providing tutorials, editing necessary web resources, distributing challenges, robustly accepting predictions, providing comprehensive access to results and analysis, and ensuring data security. The CAGI Lead Scientist will organize the CAGI conference culminating each experiment, at which results are initially presented. He or she will take a lead role in working with participants to produce publications about CAGI experiments and make presentations to ensure broad dissemination.
Additional Responsibilities: The CAGI Lead Scientist will write papers describing research findings; create effective figures, slides, and posters; and present research including travel as appropriate. He or she will apply for fellowships, grants, and engage in other career development activities. He or she will work collaboratively in the research group and provide mentorship. The CAGI Lead
Scientist is encouraged to promote diversity in science both in the lab and through outreach participating in weekly group and subgroup meetings; and performing lab jobs to facilitate lab operations. The CAGI Lead Scientist must also follow all institutional and laboratory policies.
The Berkeley academic environment The Brenner Laboratory is an interdisciplinary research group at the University of California, Berkeley, one of the world's premiere research universities. We are associated with the Department of Plant and Microbial Biology, the Department of Molecular and Cell Biology, the Department of Bioengineering, Center for Computational Biology, the California Institute for Quantitative Biosciences, as well as the University of California, San Francisco, and Lawrence Berkeley National Laboratory.
The University of California, Berkeley ranks first nationally in the number of graduate programs in the top 10 in their fields, according to the most recent National Research Council study and it was rated world's top public and fourth-best overall university according to the News U.S. latest World Report's Best Global University Rankings. Berkeley is committed to diversity in its staff, faculty, and student body, and invites all qualified people to apply, including minorities and women, veterans and individuals with disabilities.
CAGI is jointly run with the Moult Laboratory at the University of Maryland. Collaborators in this project include members of the Berkeley Center for Computational Biology, biologists and engineers at Tata Consulting Services, and clinicians at UCSF. The CAGI experiment engages a vibrant community. In addition to predictors, it includes dataset providers, advisory board and council, and assessors: Advisory Board: Russ Altman, George Church, Tim Hubbard, Scott Kahn, Sean Mooney, Pauline Ng, Susanna Repo; Scientific Council: Patricia Babbitt, Atul Butte, Garry Cutting, Laura Elnitski, Reece Hart, Ryan Hernandez, Rachel Karchin, Robert Nussbaum, Michael Snyder, Shamil Sunyaev, Joris Veltman, Liping Wei; Data providers: Adam P. Arkin, Madeleine Price Ball, Jason Bobe, George Church, Andre Franke, Nina Gonzaludo, Emma D'Andrea, Lisa Elefanti, Joe W. Gray, Linnea Jannson, John P. Kane, Pui- Yan Kwok, Rick Lathrop, Angel C. Y. Mak, Mary J. Malloy, Chiara Menin, John Moult, Robert Nussbaum, Lipika R. Pal, Clive R. Pullinger, Jasper Rine, Maria Chiara Scaini, Jeremy Sanford, Nicole Schmitt, Jay Shendure, Michael Snyder, Tim Sterne-Weiler, Paul L. F. Tang, Sean Tavtigian, Silvio Tosatto; Assessors: Rui Chen, Roland Dunbrack, Iddo Friedberg, Gad Getz, Rachel Karchin, Alexander Morgan, Sean Mooney, John Moult, Robert Nussbaum, Jeremy Sanford, David B. Searls, Artem Sokolov, Josh Stuart, Shamil Sunyaev, Sean Tavtigian, Silvio Tosatto. The CAGI Lead Scientist will interact with all CAGI participants.
Minimum Basic Qualifications required at the time of application:
Ph.D., M.D. or equivalent in computational biology, human genetics, or a related discipline.
Additional Qualifications required by start date of employment:
Demonstrated ability to work and communicate with an extensive array of collaborators.
Strong positive references.
Preferred Qualifications Desired:
Experience in managing large data sets, developing standard and automated assessment protocols, managing data set QC, performing human genetic data analyses, ethics of human research participants, publishing in high quality journals, event organization.
Ability to manage multiple and conflicting obligations and deadlines.
Our Facilities: The candidate will work in a Koshland Hall Laboratory led by Professor Brenner at the University of California, Berkeley.
Appointment Yearly Salary Range: Salary will be commensurate with experience. This is full-time (100%) or part time (85%) position. The initial appointment is for one-year with the possibility of renewal based on performance and availability of funding.
Research statement (summary of research interests and vision for CAGI)
Contact information for three to five references
Letters of reference are not required at this time. We will seek your permission before contacting your references. All letters will be treated as confidential per University of California policy and California state law. Please refer potential referees, including when letters are provided via a third party (i.e., dossier service or career center), to the UC Berkeley statement of confidentiality: http://apo.berkeley.edu/evalltr.html.
This position will be open until filled. If you have any difficulty uploading your application or any questions, please email Maria Ruiz at firstname.lastname@example.org.
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, sexual orientation, gender identity, national origin, disability, age or protected veteran status. For the complete University of California nondiscrimination and affirmative action policy see: http://policy.ucop.edu/doc/4000376/NondiscrimAffirmAct.
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