The Social & Decision Analytics Division (SDAD) is seeking applications for research faculty positions in statistical sciences. SDAD is a leading research division of the Biocomplexity Institute & Initiative (BII) at the University of Virginia. BII performs world-class informatics research in life sciences, social sciences, and human health by integrating theory, modeling and simulation with computational and experimental science in a transdisciplinary, team science research environment.
SDAD combines expertise in statistics and social and behavioral sciences to develop evidence-based research and quantitative methods to inform policy decision-making and evaluation. The researchers at SDAD span many disciplines including statistics, economics, sociology, psychology, political science, policy, health IT, public health, program evaluation, and data science.
SDAD researchers address complex social problems by leveraging the diversity of data flows available today including administrative and government records, surveys, social media, and sensors. Through team collaboration, the research faculty candidate is expected to develop the capacity to discover, repurpose and redirect these data flows to solve critical social problems. Computational complexity is at the heart of SDAD research and SDAD leverages all the research capability of BII, along with the High Performance Computing infrastructure.
The position will be offered at the rank of assistant or associate research professor and will be located in BII's location in Arlington, VA. Position reports to Sallie Keller, Director of SDAD and Professor of Public Health Sciences.
This is an open rank posting for research faculty (assistant or associate) positions and requires a PhD with relevant professional experience and appropriate credentials befitting the professorial ranks.
Responsibilities: (for all ranks unless otherwise specified)
Contributes to the development and implementation of social, behavioral, and decision analytics with a special emphasis on statistical methods.
Participates in (journey level ranks) and leads (advanced and senior level ranks) applied case studies.
Advises and coaches project team on challenging statistical and quantitative social science design, analysis and decision-making issues (for advanced and senior level ranks).
Provides expert opinions, performs statistical modeling and analyses, and leverages external experts to provide help on projects (for senior level ranks).
Collaborates with and provides statistical science expertise to team science members including students, postdoctoral fellows, faculty, and sponsors on relevance and interpretation of analyses.
Provides leadership and guidance as the statistical expert on a project team, with general direction from the PI (for senior level ranks).
Accountable for all statistical sciences aspects of the project studies and submissions, including quality, relevance and scientific validity (for advanced and senior level ranks).
Mentors undergraduate, graduate students and post docs in the SDAD (for advanced and senior level ranks).
Leads (for senior level ranks) and collaborates in (for all ranks) publication of scientific results in peer reviewed journals, professional conferences and other forums.
Engages in collaborative work with peers both within the group and outside with the aim to achieve the above objectives.
Routinely communicates research progress with supervisor, peers and other appropriate staff.
Leads (for advanced and senior level ranks) or participates (for all ranks) in seeking and preparing grant writing initiatives.
Participate fully in the intellectual life of the division and institute, and in the building of the division's reputation in research and academics.
Qualifications: (for all ranks unless otherwise specified)
Ph.D. in statistics or in a very closely related field.
Credentials equivalent at assistant or associate rank.
Ability to excel in a highly collaborative team science environment.
Experience with advanced approaches to statistics and data-driven model development.
Fluent in at least one statistical coding environment (e.g. R, Python/Pandas).
Comfort with coding in at least one non-statistical language (e.g. Python, Java, C++).
Experience using SQL to interact with relational databases (e.g. Postgres, SQL Server, Oracle).
Experience conducting spatial analyses using a dedicated GIS application or common statistical libraries (e.g. sf, Geopandas).
Communication and team science skills:
Demonstrated strong communication skills, both oral and written.
Experience in developing peer-reviewable publications and evidence of publications in peer-reviewed journals.
Strong work ethic and ability to work individually as well as within high-performing and diverse team structures.
Dependent on experience and seniority level, must possess appropriate level of independence.
Preferences: (for any rank unless otherwise specified)
Experience with using many sources of data, both traditional ones such as surveys, and non-traditional ones such as administrative data, unstructured data, images, sensors, and social media.
Experience working with federal, state, and local government entities (required for senior and advanced level ranks).
Please apply online here and complete an application and attach a cover letter, 2-page research statement, curriculum vitae, and have three confidential letters of reference sent to this email address: SDADjobs@virginia.edu.
Review of applications is ongoing and will continue until the positions are filled.
These positions will be located in Arlington (Rosslyn) VA.
For further information regarding the position please contact Savanna Galambos via email at email@example.com. For questions about the application process, please contact Ashley Cochran via email firstname.lastname@example.org.
This is a restricted position based upon the continued availability of funding. The University will perform background checks on all new hires prior to employment. This position will also require an Education Verification (FSAKA).
The University of Virginia, including the UVA Health System and the University Physician’s Group are fundamentally committed to the diversity of our faculty and staff. We believe diversity is excellence expressing itself through every person's perspectives and lived experiences. We are equal opportunity and affirmative action employers. All qualified applicants will receive consideration for employment without regard to age, color, disability, gender identity or expression, marital status, national or ethnic origin, political affiliation, race, religion, sex (including pregnancy), sexual orientation, veteran status, and family medical or genetic information.
Internal Number: R0012065
About Biocomplexity Institute and Initiative
The Biocomplexity Institute and Initiative at the University of Virginia integrates scientific research – from genetic sequencing to policy analysis – to tackle the complex task of understanding massively interacting systems and predict solutions to issues impacting human health, well-being, and habitat.
As pioneers in biocomplexity, we understand that interactions at the micro level can produce significant effects on the macro scale. We collaborate across many disciplines to discover connections between health, information networks, security and infrastructure.
The foundation of our methodology lies in information biology; the synthesis of mathematics, computation, informatics, and biology. We approach complex problem solving by assembling teams of experts in a variety of fields to work together to create solutions that challenge the very fields in which the teams operate.
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