This job has Expired
Post-Doc Research Associate
Job Description
Posting Information
Posting Details
Department | Biostatistics - CSCC - 462002 |
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Posting Open Date | 05/10/2023 |
Application Deadline | |
Open Until Filled | Yes |
Position Type | Postdoctoral Scholar |
Position Title | Post-Doc Research Associate |
Vacancy ID | PDS003848 |
Full-time/Part-time | Full-Time Temporary |
Hours per week | 40 |
FTE | 1 |
Work Location | Chapel Hill, NC |
Position Location | North Carolina, US |
Hiring Range | |
Proposed Start Date | |
Estimated Duration of Appointment | 12 Months |
Position Information
Primary Purpose of Organizational Unit | The Department of Biostatistics (BIOS) is internationally recognized as a leader in Biostatistics research and training. It is one of eight departments in the Gillings School of Global Public Health whose mission is to improve the health and wellbeing of the population. This mission is accomplished through the interaction of teaching, research and service. The department is one of the largest, most complex departments on campus. For FY19, Biostatistics, was 4th among all departments and centers across campus in research funding at UNC Chapel Hill and currently has almost 300 employees. The Department operates a $46 million sponsored research budget (FY19), a 1.7-million-dollar state budget, a 1.0-million-dollar F&A budget and spends roughly 3.0 million in trust funds annually. The Department has 55 EHRA and EHRA Non-Faculty members, 74 permanent staff members and 162 temporary employees. The Department has 235 students (184 graduate students and 51 undergraduate students). The Department of Biostatistics is housed in three different locations: administrative and faculty offices, including a suite of offices for graduate students in McGavran-Greenberg Hall; the Collaborative Studies Coordinating Center (CSCC) at Carolina Square; and the Carolina Survey Research Laboratory (CSRL) at Bolin Creek Center. |
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Position Summary | A post-doctoral position is available for a qualified candidate for applied and methodological research in precision health, deep learning and machine learning, with particular attention to deep learning applied to both medical imaging and EKG data, and other signal data as well as clinical data. We are particularly interested in applied and methodological research on how to effectively combine signal/image/natural language processing with machine learning to develop prediction tools and to estimate optimal dynamic treatment regimes (DTRs) as well as other precision medicine inferences, with a goal for the results to be useful in global health in under resourced locations. The position will work with the Departments of Biostatistics and OB/GYN. |
Minimum Education and Experience Requirements | The candidate should have a PhD or equivalent doctorate (e.g., Sc.D.) in computer science, statistics, biostatistics, operations research, or a related quantitative field. |
Required Qualifications, Competencies, and Experience | Doctoral degree. |
Preferred Qualifications, Competencies, and Experience | Background in computer science, statistics, machine learning, causal inference, and applications of deep learning to biomedical data. |
Special Physical/Mental Requirements | |
Special Instructions | For information on UNC Postdoctoral Benefits and Services click here |
Quick Link | https://unc.peopleadmin.com/postings/256541 |
Posting Contact Information
Department Contact Name and Title | Annette Raines, HR Consultant |
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Department Contact Telephone or Email | annette_raines@unc.edu |
Postdoctoral Affairs Contact Information | If you experience any problems accessing the system or have questions about the application process, please contact the University’s Equal Employment Opportunity office at (919) 966-3576 or send an email to equalopportunity@unc.edu. Please note: The Equal Employment Opportunity office will not be able to provide specific updates regarding position or application status. |
Equal Opportunity Employer Statement | The University of North Carolina at Chapel Hill is an equal opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to age, color, disability, gender, gender expression, gender identity, genetic information, race, national origin, religion, sex, sexual orientation, or status as a protected veteran. |
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