Data
Science Postdoctoral Associate Position Department
of Population Medicine and Diagnostic Sciences College
of Veterinary Medicine Cornell
University Ithaca,
NY
This is a data science
postdoctoral position with the Cornell Wildlife Health Lab (CWHL). The CWHL is
a 10-member laboratory in the Department
of Population Medicine and Diagnostic Sciences at the Cornell University College
of Veterinary Medicine in Ithaca, New York, USA. The scope of CWHL’s research
spans wildlife health issues across North America, and our scientists collaborate
with researchers and agency representatives from academic institutions, state
and provincial wildlife agencies, and federal natural resource agencies.
This postdoctoral position
will work 100% FTE on the Surveillance Optimization Project for Chronic Wasting
Disease (SOP4CWD) https://cwhl.vet.cornell.edu/project/sop4cwd. The SOP4CWD is multi-year
modeling and big data endeavor that leverages traditional and new techniques in
data and statistical science to generate data-driven recommendations for
surveillance sampling of chronic wasting disease (CWD) in white-tailed deer. The modeling outputs will guide managerial activities aimed to monitor
and manage the spread of CWD through deer populations in the eastern US and
Canada.
Phase 1 of SOP4CWD requires the setup,
calibration, and execution of traditional and novel computational models for
epidemiological research for delivery of sampling recommendations to
participating states and provinces. Phase 2 of SOP4CWD requires the development
of the Data Dashboard, an interactive, online repository of model outputs and graphics
that communicate the data-driven surveillance recommendations to wildlife
agency representatives. Phase 3 of SOP4CWD
requires the development of the Data Warehouse, a region-wide repository of
disease, demographic, hazard, and risk data as generated and provided by the
participating state and provincial wildlife agencies. Phase 4 of SOP4CWD
requires the development of the “autonomous computational pipeline” that links
the software products and informational transfer among Phases 1-3.
At the time of this
posting, the SOP4CWD collaboration has gathered data from over a dozen state
and provincial wildlife agencies. The goal of the
project is to forge cross-jurisdiction cooperation among wildlife agencies. As
such, in addition to the overall research goals, there exist countless unforeseeable
logistical and mechanical puzzles needing clever solutions to mesh the data, its
storage, the models, and their outputs into and out of the pre-existing managerial
infrastructure that may or may not be consistent across agency jurisdictions.
The primary project goal is to produce a single, cohesive, useful, and
user-friendly system.
If you like thinking
through and solving diverse puzzles from simultaneous perspectives of ecology,
wildlife, disease, statistics, mathematics, computer science, data management,
and natural resource management, then this position is for you!
As a postdoctoral
associate, some of your specific duties will include:
- Design, engineer, and/or improve existing workflow
software that transfer information from its raw form into a format usable
for local, state, or regional scientific analysis and communication. This
includes the design and creation of repeatable and scientifically sound data
cleaning, standardization, and/or processing workflows for data that
originates from the agency in any raw form. Workflow software should
produce structural outputs of data that satisfy the formatting requirements
necessary for immediate (and autonomous) upload into several statistical
and/or algorithmic models. Workflow software must also include the
detailed debugging of command codes and annotated comments such that the software
may be replicated by other programmers and can be used to autonomously clean
and format data as it is submitted to the Data Warehouse by participating
state and provincial agencies.
- Develop data visualization tools to illustrate model
outputs including maps, tables, graphs, and narratives that aid
interpretation of the models and teach users about the quantitative
processes.
- Develop and implement novel statistical modeling and/or
algorithmic approaches to integrate convenience, observational, and/or
limited wildlife disease data into pre-existing and/or novel mathematical
models to advance knowledge and prediction of wildlife diseases.
- Develop software that autonomously links new and
existing R code of mathematical and/or statistical models into a single,
cohesive, robust computational pipeline, which is capable of seamlessly importing
data from the Data Warehouse and exporting modeling results to the
Warehouse and Dashboard.
- Edit pre-existing R software to reduce runtime of user
interface or algorithms through parallelization and/or modularization of
code and/or through other modifications of codes as appropriate and/or
applicable.
- Develop software to ensure privacy of sensitive data
and research outputs, including the development of log-in pages and/or the
development of secure computational linkages between the Data Warehouse,
the models, and the Data Dashboard.
- Generate collaborative research outputs (scientific publications,
software, outreach materials, grant applications, and/or presentations) that
develop and/or communicate software, data science techniques, mathematical
techniques, and/or new statistical techniques to advance the field of wildlife
disease, to aid in prediction, reproducibility, and communication of
scientific knowledge of the field, and to increase quantitative
infrastructures available to researchers in the fields of resource
management, ecology, wildlife, and/or wildlife diseases.
- Communicate research findings to all audiences, including
the development of materials that are understandable to persons with
education levels ranging from high school through doctorate in fields that
may or may not include wildlife disease, wildlife management, or
ecology.
- Independently, or with a team, execute all stages of the
scientific publication process, including the initial draft, submission,
revisions, finalization, and promotion of the products to contribute to
the body of knowledge in the scientific field.
- Participate in steering, planning, and/or project
update meetings with the CWHL and collaborators and work closely with personnel at the CWHL, and as needed with
other project partners including modelers, researchers, programmers, and
agency representatives of partnering entities.
- Other duties as assigned.
As a postdoctoral
associate, you must:
·
Have the ability to
work independently and make scientifically sound and defensible modeling and/or
software programming decisions with the highest
scientific integrity.
- Be
a self-starter, capable of meeting deadlines and keeping your project responsibilities
on track for on-time completion from your remote location.
- Be
comfortable asking for assistance from others and/or providing others with
assistance if asked.
- Be
willing to work with and collaborate effectively with a diverse community
of professionals that may or may not understand the technical details of
the methods, procedures, or infrastructures of the quantitative field.
- Have
a problem-solving attitude.
Required
Qualifications:
- PhD in Statistical
Science, Data Science, Computer Science, or related field.
- Fluency in R and R
Studio.
- Proficiency in the
development/maintenance of databases, data storage, processing, and APIs.
- Proficiency in data
security, including the appropriate handling of sensitive data, and the
maintenance of data privacy throughout all computations and workflows.
- Interest in the
creative development of quantitative infrastructure capable of leveraging existing
sources of opportunistic and/or incomplete wildlife data sets to aid in the
advancement of the use of available data in natural resource management
decisions.
- The ability to invent creative
yet scientifically sound ways to think through and overcome obstacles with missing
and/or incomplete data in both small and large scopes.
- Willingness to teach
yourself what you need to know to complete your duties, but capable of asking
for help if you run into a dead end.
- Your own computer,
workstation, and reliable internet connection.
- Tenacity to solve
novel and unforeseen scientific problems, big and small.
Preferred Additional
Qualifications: - Proficiency in the
field or application of ecological mathematical modeling, such as familiarity
and/or facility with agent-based or population-based ecological models.
- Proficiency in R Shiny
and the development of web site interactive applications.
- Previous education
and/or professional experience in boots-on-the-ground wildlife disease,
wildlife, ecology, natural resource management settings, with field experience that
included data collection and/or the participation in management discussions a particular
plus.
- Proficiency in Net
Logo and/or the running of computational simulations as an experimental
methodology.
- Dedication to a career
track in wildlife and/or natural resources management.
For more information
on SOP4CWD, contact Dr. Krysten Schuler at the CWHL (cwhl@cornell.edu) or visit https://cwhl.vet.cornell.edu/project/sop4cwd
Timeline: Applications will be reviewed on a
rolling basis and position start is flexible, but ideally would be on-board by
6/2021. Position is funded for 1 year with the possibility of extension if
additional funding is secured, and successful performance.
To Apply: Visit https://academicjobsonline.org/ajo/jobs/18043 to submit a cover letter, curriculum vitae, contact
information for three references, and a research statement.
Location:
Ithaca, NY. The opportunity to work remotely will be reviewed and decided
upon approved US domestic locations that meet all liability and compensation
policies.
Employment Assistance:
For specific questions about the position or application process, please contact the Recruiter listed in the job posting or for general questions email mycareer@cornell.edu.
If you require an accommodation for a disability in order to complete an employment application or to participate in the recruiting process, you are encouraged to contact Cornell University's Office of Institutional Equity and Title IX at voice (607) 255-2242, or email at equity@cornell.edu. Applicants that do not have internet access are encouraged to visit your local library, or local Department of Labor. You may also request an appointment to use a dedicated workstation in the Office of Talent Attraction and Recruitment, at the Ithaca campus, by emailing mycareer@cornell.edu. Please read the required Notice to Applicants statement by clicking here. This notice contains important information about applying for a position at Cornell as well as some of your rights and responsibilities as an applicant. EEO Statement: Diversity and Inclusion are a part of Cornell University’s heritage. We are a recognized employer and educator valuing AA/EEO, and we do not tolerate discrimination based on any protected characteristic, including race, ethnic or national origin, citizenship and immigration status, color, sex/gender, pregnancy or pregnancy-related conditions, age, creed, religion, actual or perceived disability (including persons associated with such a person), arrest and/or conviction record, military or veteran status, sexual orientation, gender expression and/or identity, an individual’s genetic information, domestic violence victim status, familial status, marital status, or any other characteristic protected by applicable federal, state, or local law. We also recognize a lawful preference in employment practices for Native Americans living on or near Indian reservations in accordance with applicable law. Cornell University embraces diversity and seeks candidates who will contribute to a climate that supports students, faculty, and staff to all identities and backgrounds. We encourage individuals from underrepresented and/or marginalized identities to apply.
Pay Ranges: The hiring rate of pay for the successful candidate will be determined considering the following criteria:
- Prior relevant work or industry experience.
- Education level to the extent education is relevant to the position.
- Academic Discipline (faculty pay ranges reflects 9-month annual salary)
- Unique applicable skills.
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