Research Faculty in Statistical and Quantitative Sciences
Biocomplexity Institute and Initiative
Location: Arlington , Virginia
Type: Full Time
Preferred Education: Doctorate
Internal Number: R0037748
The Social & Decision Analytics Division (SDAD) seeks applications for research faculty positions in statistical and quantitative sciences. SDAD is a leading research division in the Biocomplexity Institute & Initiative (BII) at the University of Virginia. BII performs world-class informatics research in life sciences, human health, and social sciences by integrating theory, modeling, and simulation with computational and experimental science in a transdisciplinary, team science research environment.
SDAD develops evidence-based research and quantitative methods to inform policy decision-making and evaluation. This thematic focus includes research partnerships with local, state, and federal agencies and communities to address their questions by integrating and linking multiple heterogeneous data sources.
SDAD researchers address complex social problems by leveraging today's diverse data flows, 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 the Biocomplexity Institute’s research capability and the High-Performance Computing infrastructure. This research includes data synthesis, integration and linkage, space-time modeling, applied and computational math, and creating data platforms and infrastructures to address program needs.
To learn more about SDAD and BII, please visit us at biocomplexity.virginia.edu.
The position will be in BII's location in Arlington, VA. The Position reports to the Division Director, Social and Decision Analytics (SDAD), Biocomplexity Institute. BI offers a flexible hybrid workplace, providing a balance of in-person and remote work for each employee. All team members must have access to and maintain a secure home office environment with high-speed internet service and work collaboratively with colleagues using a variety of technologies and tools. Due to the collaborative nature of our work, team members are expected to be present and attend team meetings and other critical functions in person. Depending on the needs of the group, or as deemed by the manager, team members may be required to work periodically in open offices, meeting rooms or other shared workspaces.
This is an open rank posting for research faculty (assistant, associate, and full) professor positions and requires a Ph.D. with relevant professional experience and appropriate credentials befitting the professorial ranks.
Applications will be reviewed on a rolling basis and remain open until filled. The start date is flexible and based upon successfully completing the recruiting process and offer negotiations.
Responsibilities: (for all ranks unless otherwise specified)
Contributes to developing and implementing statistical theory and methods for BII research.
Advises and coaches project team on challenging statistical and mathematical design and analysis issues
Collaborates with and provides statistical science expertise to team science members, including students, postdoctoral fellows, faculty, and sponsors, on relevance and interpretation of analyses.
Mentors undergraduate, graduate students, and postdocs in the
Leads and collaborates in the 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 to achieve the above objectives.
Routinely communicates research progress with supervisor, peers, and other appropriate staff.
Leads or participates in seeking and preparing grant writing initiatives.
Participate fully in the intellectual life of the division and institute and build the division's reputation in research and academics.
Qualifications: (for all ranks unless otherwise specified)
Ph.D. in statistics or in a closely related field.
Credentials equivalent at the assistant, associate, and full professor
Ability to excel in a highly collaborative team science environment.
Experience with advanced approaches to statistics and data-driven model development.
Fluent in statistical coding environments (e.g., R, Python/Pandas)
Comfort with coding in non-statistical languages (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., R sf package, Geopandas)
Communication and team science skills:
Demonstrated effective 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 and within high-performing and diverse team structures.
Depending on experience and seniority level, one must possess an appropriate level of independence.
Additional responsibilities and qualifications for associate and full-professor ranks:
Provides expert opinions, performs statistical modeling and analyses, and leverages external experts to provide help on projects
Provides leadership and guidance as the statistical expert on a project team, with general direction from the PI.
Successful track record in obtaining external funding and publication record.
Evidence of emergent or national reputation.
Accountable for all statistical sciences aspects of the project studies and submissions, including quality, relevance, and scientific validity.
Experience with using many data sources, both traditional ones such as surveys and non-traditional ones such as administrative data, unstructured data, images, sensors, and social media.
Experience with data synthesis, data integration and linkage, space-time modeling, numerical linear algebra, demography, and creating data infrastructures to address program needs.
Experience working with foundations, and/or federal, state, and local government entities
Anticipated Hiring Range: Rank and compensation are commensurate with candidate's experience, qualifications, and rank, with UVA benefits.
Complete an application online through Workday and attach the following:
2-Page Research Statement
Contact Information for three (3) references
Multiple documents may be uploaded into the CV/Resume box. Alternatively, you may merge all documents into one PDF. Applications that do not contain all the required documents will not receive full consideration.
All roles within the institute are restricted positions and are dependent upon project need, availability of funding, and performance.
This position will remain open until filled. This is an Exempt level, benefited position.
The University will perform background checks on all new hires prior to employment.
This position also requires an Education Verification (FSAKA).
Questions related to the positions may be directed to Savanna Galambos, Special Assistant for Administrative Affairs, email@example.com.
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.