As part of the university's comprehensive vaccination program, all Cornell employees are required to have and provide proof of an FDA-or WHO-authorized or approved COVID-19 primary vaccination or have obtained a university-approved disability/medical or religious exemption, regardless of their role and work location.
New hires are required to provide documentation showing primary vaccination status (that is, completion of two shots of the Moderna or Pfizer vaccine or one shot of the Janssen/Johnson & Johnson) before their first day of work. If a new hire's vaccination is not complete or information is not received by their start date, the first day of work will be delayed. It is possible in some cases that an offer of employment may be withdrawn.Postdoctoral
Associate Position in Computational Approaches to Antimicrobial Resistance
Surveillance Dr. Casey Cazer Department of Public and Ecosystem Health College of Veterinary Medicine, Cornell University Ithaca, NYThe Cazer Lab in the Department of Public and Ecosystem
Health, Cornell University College of Veterinary Medicine is seeking an
outstanding postdoctoral associate in the area of antimicrobial resistance
surveillance, using methods from computational biology, machine learning, and
statistics.
The Cazer Lab broadly investigates the epidemiology of
zoonotic and infectious diseases with computational and field studies. We are
primarily interested in the development and spread of antimicrobial resistant
bacteria among animals and humans. Specifically, we are investigating novel
computational approaches to antimicrobial resistance surveillance to detect
increases in resistance and quantify the impacts of mitigation approaches, such
as antimicrobial use restrictions in livestock. We also have projects
investigating syndromic surveillance for COVID-19 in institutional and
community settings, as well as the prevalence and persistence of immunity
post-vaccination and post-natural infection.
The
postdoctoral associate will work primarily on multidrug resistance surveillance.
Multidrug resistance complicates treatment of bacterial infections, therefore
early knowledge of circulating resistance phenotypes can improve patient level
outcomes and judicious antimicrobial use. However, the number of potential
multidrug resistance patterns is exponentially large. We use association
mining, an unsupervised machine learning method, to identify and quantify
multidrug resistance patterns in phenotypic antimicrobial resistance data. We
plan to incorporate genomic sequencing data into this surveillance approach and
are interested in exploring new machine-learning techniques for multidrug
resistance surveillance in human and animal populations.
There
will be opportunities to develop independently driven projects on infectious
diseases and the intersection of epidemiology and machine learning. We have
access to laboratory diagnostic results, veterinary and human medical records,
and national antimicrobial resistance surveillance data. Qualified candidates
will have opportunities to supervise graduate, veterinary, and undergraduate
students. Responsibilities: - Develop analytic pipelines for
multidrug resistance analysis using association mining and/or other
unsupervised machine learning techniques
- Examine correlations between
genotypic and phenotypic resistance patterns
- Collaborate with subject matter
experts in antimicrobial resistance and microbiology
- Draft manuscripts and publish
results in high-quality, peer-reviewed journals
- Use best-practices for
reproducible coding
- Present results at conferences and
seminars
- Contribute to developing and
writing grant proposals
Qualifications: - Ph.D. degree in Biostatistics, Bioinformatics,
Applied Statistics, Computer Science, Mathematics, or a related discipline or a
health professional doctorate (e.g., DVM, MD) with substantial experience in one
of these fields.
- Experience working with biomedical
data preferred.
- Knowledge of epidemiologic
principles preferred.
- Must be able to work independently
and as part of a diverse, interdisciplinary team.
- Strong analytic and written
communication skills are required.
- Proficiency in R (preferred) or
other data analysis software
This is a 1-year,
full-time appointment with a potential for extension contingent on funding and
successful performance. This position will start immediately, and work may be
conducted partially or fully remotely.
To apply, visit https://academicjobsonline.org/ajo/jobs/20860 to submit a cover letter, curriculum
vitae, contact information for three references, and a research statement.
If
you have any questions regarding this posting, please contact Dr. Casey Cazer (clc248@cornell.edu).
The Department of Public and Ecosystem Health mission is to
use a transdisciplinary, systems approach to tackle the world’s most pressing
challenges that involve the inter-dependent health of people, animals, and the
ecosystems on which all life depends. Rather than organize around a common
discipline or approach, Public & Ecosystem Health brings public health
professionals, biophysical and social scientists, and veterinarians together to
address three of the world’s greatest challenges: achieving healthy food
systems, tackling emerging health threats, and conserving biodiversity. We seek
not only to understand these wicked problems through research, but also to
address them directly through public health and clinical veterinary practice.
Quite simply, our students, staff, and faculty seek to change the world. To do
this, we utilize a transdisciplinary One Health/Planetary Health systems
approach, and base our work in the principles of sustainability, equity, and
engagement.
Diversity and Inclusion are a part of Cornell University’s heritage. We are a recognized employer and educator valuing AA/EEO, Protected Veterans and Individuals with Disabilities. We also recognize a lawful preference in employment practices for Native Americans living on or near Indian reservations. Cornell University is an innovative Ivy League university and a great place to work. Our inclusive community of scholars, students, and staff impart an uncommon sense of larger purpose, and contribute creative ideas to further the university's mission of teaching, discovery, and engagement. |