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Research Associate, Center for Diabetes Technology (UVA)

Job Description


The Center for Diabetes Technology (CDT) and the University of Virginia (UVA) School of Medicine invites applicants for multiple Postdoctoral Research Associates for their research team, focusing on highly complex technology, algorithm development and data management and analysis. CDT is a recognized world leader in the technological treatment of diabetes and the hub of an international research network of leading U.S. institutions. We advance the use of technology, including analytics, to allow improved data and operational management, monitoring, and therapies for patients with Type 1 and Type 2 Diabetes. The Postdoctoral Research Associates will report to Marc Breton, PhD.  Dr. Marc Breton was chosen as the recipient of the 2022 Edlich-Henderson Innovator of the Year award. Teaming with Dr. Boris Kovatchev, Breton went on to create the first – and to date only – simulation environment accepted by the U.S. Food & Drug Administration as a replacement for animal studies in pre-clinical assessment of insulin treatment strategies. It paved the way for the pair’s invention of a revolutionary artificial pancreas that could monitor and automatically regulate a person’s blood glucose levels. Overall, Breton has submitted 55 invention disclosures to LVG since 2007, and he is a named inventor on 27 issued U.S. patents. Today, the work that Breton started when he was a post-doc nearly 20 years ago continues to improve the lives of people with diabetes around the world. His work epitomizes UVA’s commitment to biotechnology and its promise of saving and improving lives.  https://news.virginia.edu/content/uva-innovator-year-marc-bretons-surprise-journey-diabetes-pioneer

The CDT is directed by Boris Kovatchev, PhD, a world-renowned researcher in the field of Diabetes, algorithm development and data science. Dr. Kovatchev is a regular lecturer at Universities and Conferences throughout the US and Europe.  He is actively involved with Center projects and with the direction and education of all post-doctoral candidates. With substantial NIH funding, the Center led and successfully completed the three largest randomized Artificial Pancreas(AP) clinical trials in the World to date , including a pivotal trial aiming for regulatory clearance of a new AP System (that included the algorithm program developed at the Center), published on October 16, 2019 in the New England Journal of Medicine .  For more information visit: https://med.virginia.edu/diabetes-technology/

 

Successful candidates will be afforded the opportunity to continue their research under the supervision of a team of accomplished faculty members and physicians. As well, incumbents will be able to conduct independent translational research in biotechnology, biomedical engineering, advanced mathematics, and Data Science that will not only be essential to the programs of CDT faculty members; but will impact future healthcare programs and therapeutics for improved patient care. Incumbents will perform high-profile, NIH-funded and other sponsored research in an interdisciplinary international research setting and be a regular attendee at diabetes and technology conferences.

Successful candidates will be expected to:

Conduct supervised and independent research for the Center for Diabetes Technology and expand Center-related research lines in:

· Use of machine learning methods for risk prediction, control, classification, and treatment progression

· Metabolic and behavioral computer simulations related to diabetes and pre-diabetes.

· Modeling, simulation and model-based analysis of glucose metabolism and control.

· Validation and testing of in silico-designed treatments and diabetes-related technology.

In addition to the above job responsibilities, other duties may be assigned.

There are no clinical responsibilities associated with this position. However, the successful candidate will have regular access to physicians through the UVA School of Medicine.

Qualified candidates must have: 

Education: Doctoral degree completed at time of hire.

 

Preferred requirements: 

Research experience in machine learning, biotechnology, biomedical engineering, advanced mathematics or (Diabetes) Data Science.

To Apply: 
Process for Internal UVA Applicants: Please apply through your Workday Home page, search “Find Jobs”, and search for R0047490.

Complete an application online with the following documents:

  • CV/Resume

  • Cover letter

  • Contact information for three references.

Upload all materials into the resume submission field, multiple documents can be submitted into this one field. Alternatively, merge all documents into one PDF for submission. Applications that do not contain all required documents will not receive full consideration. 

Process for External Applicants: Please visit UVA job board at https://uva.wd1.myworkdayjobs.com/UVAJobs and search for R0047490.

Complete an application online with the following documents:

  • CV/Resume

  • Cover letter

  • Contact information for three references.

Upload all materials into the resume submission field, multiple documents can be submitted into this one field. Alternatively, merge all documents into one PDF for submission. Applications that do not contain all required documents will not receive full consideration. 

Priority review of applications will begin on May 8, 2023, but the position will remain open until filled.  This position will sponsor applicants for work visas.  This is a restricted position; continuation is dependent on funding and satisfactory performance. This position is located in Charlottesville, Virginia. This is a full-time benefited position.  For more information on the benefits at UVA, visit www.hr.virginia.edu/benefits.  

References will be completed via UVA’s standardized process Skill Survey. A total of five references will be requested via SkillSurvey during the final phase of the interview process. The University will perform background checks on all new hires prior to employment. A completed pre-employment health screen is required for this position prior to employment.  

For questions about the application process, please contact Christi Maguire, Recruiting Specialist, at clm8sd@virginia.edu. For questions regarding the position, please contact Dr. Marc Breton, Associate Professor, at mb6nt@virginia.edu. For more information about UVA and the Charlottesville community, please see http://www.virginia.edu/life/charlottesville and https://embarkcva.com/.
 

Physical demands: This is primarily a sedentary job involving extensive use of desktop computers. The job does occasionally require traveling some distance to attend meetings, and programs.

 

Postdoctoral employment is temporary and is normally limited to an individual who has been awarded a Ph.D. or equivalent doctorate within the previous five years and who will be involved in full-time research or scholarship at the University. Employment as a Postdoctoral Research Associate is viewed as training and is preparatory for a full-time academic or research career, is supervised by a senior scholar and allows the appointee to publish the results of his/her research or scholarship during the training period.


COVID Vaccination Requirement and Guidelines

Please visit the UVA COVID-19 Job Requirements and Guidelines  webpage prior to applying for current information regarding vaccination requirements?and?guidelines for employment at UVA.

The University of Virginia, i ncluding the UVA Health System which represents the UVA Medical Center, Schools of Medicine and Nursing, UVA Physician’s Group and the Claude Moore Health Sciences Library, are fundamentally committed to the diversity of our faculty and staff.  We believe diversity is excellence expressing itself through every person's perspectives and lived experiences.  We are equal opportunity and affirmative action employers. All qualified applicants will receive consideration for employment without regard to age, color, disability, gender identity or expression, marital status, national or ethnic origin, political affiliation, race, religion, sex (including pregnancy), sexual orientation, veteran status, and family medical or genetic information.


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