Assistant Professor (12MO), Biostatistics

SUNY Downstate Health Sciences University; New York (NY); On-site; USD 90,000 - 130,000; Full time

Job summary

The Department of Epidemiology & Biostatistics in the School of Public Health at SUNY Downstate Health Sciences University seeks a full-time Assistant Professor (12MO). The successful candidate will teach biostatistics to masters and doctoral students, mentor MPH and doctoral students, and provide biostatistics support across the university.

They will engage in a focused research area and contribute to program development and data-oriented collaborations.

Qualifications

• Terminal degree (PhD/MD/ScD) required.
• Experience teaching Data Science courses and program development at institutional level.
• Expertise in biostatistics methods across hierarchical, longitudinal, survey, and big data contexts.

Responsibilities

• Teach biostatistics courses to masters and doctoral students.
• Mentor MPH and doctoral students.
• Provide biostatistics support to faculty across SUNY Downstate Health Sciences University.
• Engage in a focused area of research.

Skills

Teaching Data Science

Program development

Biostatistics support

Data display

Spatial analysis

Longitudinal data

Survey data

Causal inference

Structural equation models

Education

Terminal degree (PhD/MD/ScD)

Job description

Job Description

The Department of Epidemiology & Biostatistics in the School of Public Health at SUNY Downstate Health Sciences University is seeking a full-time Assistant Professor (12MO). The successful candidate will:

• Teach biostatistics courses to masters and doctoral students.
• Mentor Master of Public Health and doctoral students.
• Provide biostatistics support to faculty in the School of Public Health and across Downstate Health Sciences University.
• Engage in a focused area of research.

Qualifications

Required Qualifications

• Terminal degree, PhD, MD, ScD.
• Experience in teaching Data Science courses, program development, and developing and managing biostatistical support at the institutional level.
• Experience with data display; spatial analysis and modeling; statistical methods for hierarchical data; longitudinal repeated-measures data; complex survey data; mixed-methods data; quasi-experimental research designs; causal inference methods such as propensity score matching methods, and structural equation models; non-parametric and semi parametric methods; statistical learning methods for prediction and classification; and/or big data analytic expertise in-omics data, imaging data, bioinformatics, and electronic health records data.
• Expertise in machine learning and AI approaches to public health research is also desirable.
• Successful attainment of extramural funding and demonstrated research expertise, as evidenced by a substantial publication record in high-quality journals.
• Or, a satisfactory equivalent combination of experience, education and training to the above.