cancer screening and surveillance data
| Position ID: | Duke-Math-PSM [#20646] |
| Position Title: | Postdoctoral Associate in Statistical Modeling of Cancer Screening and Surveillance Data |
| Position Type: | Postdoctoral |
| Position Location: | Durham, North Carolina 27708, United States [map] |
| Subject Areas: | longitudinal data analysis cancer screening and surveillance data |
| Appl Deadline: | finished (2022/05/10, finished 2022/12/13, listed until 2022/08/31) |
| Position Description: |
| The
Ryser
Laboratory
at Duke
University
(Durham,
NC, USA) is looking for a highly motivated Postdoctoral Associate in
the fields of longitudinal data analysis and joint modeling of cancer
screening and surveillance data. The
position will be funded by Marc
D. Ryser,
PhD who holds a joint appointment between the Departments Population
Health Sciences
and Mathematics.
The
appointment is for 2 years and may be renewed for 1 year.
Overview. The successful applicant will use tools from statistics, biostatistics and mathematics to analyze and model rich longitudinal datasets from breast and brain cancer patients. Possible projects include (i) model-based inference of breast cancer overdiagnosis from a large longitudinal mammography registry; (ii) joint modeling of surveillance patterns and disease recurrence in a large, newly established cohort of patients diagnosed with early-stage breast cancer; and (iii) joint modeling of surveillance imaging (MRI) and disease progression in low-grade glioma patients. All three projects will require a certain degree of applied methods development. The work will be performed in a cross-disciplinary setting, together with clinical collaborators. Qualifications. The successful applicant has a doctorate in (bio)statistics, applied mathematics, epidemiology, or a related discipline. The position requires proficiency in stochastic processes, longitudinal data analysis, joint modeling of longitudinal processes, and Bayesian inference techniques. Extensive experience with real-world (cancer) data and advanced statistical programming skills are required. The successful applicant demonstrates great attention to detail, works independently, takes initiative, has excellent written and verbal communication skills, and performs well in an interdisciplinary environment at the interface between the quantitative sciences and medicine. The successful candidate is expected to have a track record of first-author publication in peer-reviewed journals. Application. Interested applicants should submit the following documents:
Completed applications will be reviewed on an ongoing basis until the position is filled. Questions may be directed to marc.ryser@duke.edu. Duke University is an Affirmative Action/Equal Opportunity Employer committed to providing employment opportunity without regard to an individual\u2019s age, color, disability, genetic information, gender, gender identity, national origin, race, religion, sexual orientation, or veteran status. Duke is committed to encouraging and sustaining work and learning environments that are free from harassment and prohibited discrimination. Duke prohibits discrimination and harassment in the administration of both its employment and educational policies. Duke University is an Affirmative Action/Equal Opportunity Employer committed to providing employment opportunity without regard to an individual's age, color, disability, genetic information, gender, gender expression, gender identity, national origin, race, religion, sex, sexual orientation, or veteran status. Duke also makes good faith efforts to recruit, hire, and promote qualified women, minorities, individuals with disabilities, and veterans. |
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