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Postdoctoral Research Associate, Data Science (Computer Vision/Machine Learning)
University of Virginia in Charlottesville, Virginia
 
 
Apply
 
Date Posted 10/22/2021
Category
Admin-Computing-Other
Employment Type FullTime
Application Deadline Open until filled
 
 
 
 
 

The Visual Intelligence Laboratory (‘Baek Lab’) at the University of Virginia School of Data Science is looking to fill multiple open positions for postdoctoral research associate to conduct both theoretical and applied research in the areas of computer vision and machine learning. Specific areas of interest include (but not limited to):

  • Human pose/motion estimation, activity recognition, human body shape modeling, sports analytics/ergonomics, performance/injury prediction, and other human factors areas
  • Computer graphics, geometric deep learning, graph neural networks, statistical shape analysis, 3D reconstruction, and other digital geometry processing applications
  • Scientific machine learning (SciML), data-driven modeling of dynamic processes, uncertainty quantification, stochastic process modeling
  • Federated learning, distributed machine learning, and distributed big data systems

Successful candidates will participate in one or more of relevant research projects sponsored by the federal government/industry partners, including the National Science Foundation, National Institutes of Health, U.S. Department of Defense, etc. Responsibilities will include conducting cutting-edge scientific research, designing novel mathematical formulae and algorithms, communicating research findings through scientific publications, developing and maintaining reproduceable software codes, and mentoring graduate students.

Successful candidates may also participate in teaching and other expanded duties if they are interested in building broader career experience.

Qualifications

  • A doctoral degree in data science, computer science/engineering, applied mathematics, or other relevant areas by the start date of the position.
  • Strong verbal/written communication skills
  • Publication record in top-tier journals/conferences
  • Proficiency in TensorFlow, PyTorch, MxNet, or other deep learning frameworks
  • Strong programming skills

This is a one-year term limited position with the possibility of renewal based on funding and satisfactory performance.


Selected candidates will be required to complete a background check prior to the first day of employment per the University policy.

Benefits include the opportunity to work in a highly multidisciplinary environment with a diverse team of researchers in data science, computer science, mechanical engineering, materials science, business analytics, medicine, and other disciplines. You will also have a chance to work with multi-institutional collaborators and to build a strong network. Competitive salary, insurance benefits, retirement funds, and other benefits will also be provided per the University policy.

To Apply

Complete an application online and attach:

  • Cover letter
  • CV
  • Three writing samples
  • Transcripts
  • Names and contact information of three referees

****Please combine all required application materials in the other listed above into one document and upload in the resume / cv box ***

PROCESS FOR INTERNAL UVA APPLICANTS : Please apply through your Workday Home page, search “Find Jobs”, and search for ‘R0029339’. Complete an application online and attach the required documents.

PROCESS FOR EXTERNAL UVA APPLICANTS : Please visit UVA job board https://uva.wd1.myworkdayjobs.com/UVAJobs , complete the application and attach the required documents.

For additional information about the position, please contact Stephen Baek at baek@virginia.edu

For information about the application process, please contact Rhiannon O’Coin at rmo2r@virginia.edu

About the School of Data Science

The University of Virginia has announced plans to establish a School of Data Science, an effort made possible in part by the largest private gift in the institution’s 200-year history. The School of Data Science – UVA’s 12th school and the first established since 2007 – will position the University as a global leader in efforts to improve society through teaching and research based on the powerful, emerging field of data science. It builds on a foundation set in place at UVA by the Data Science Institute (DSI), a pan-University institute established in 2013 that grants graduate degrees and has a dual mission in education and research.


COVID Vaccination Requirement
 

The University of Virginia expects all current and new employees (UVA Health System and Academic), to be vaccinated against COVID-19. 
 
If hired to work within the University Health System, you will be required to provide proof of vaccination or be willing to receive the vaccination. Employees may request a medical or religious exemption from vaccination.
 
If hired to work on the Academic side of the University, excluding the School of Medicine, School of Nursing, UPG, and the Health Systems Library, you will be required to provide proof of vaccination or be willing to submit to mandatory, weekly prevalence testing. Employees that are working 100% remotely will not be subject to weekly prevalence testing; however, if the employee works on UVA Grounds (including the Medical Center) even intermittently, then they are required to be tested for COVID-19 once per week on an indefinite basis and follow masking mandates. 
 
NOTE: Some medical and safety-sensitive positions require vaccination and are not eligible for an exemption.  For more information on how the vaccination and testing requirements will apply to you at your work location, see the UVA New Hire Vaccination Requirements webpage. 

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.



The Visual Intelligence Laboratory (‘Baek Lab’) at the University of Virginia School of Data Science is looking to fill multiple open positions for postdoctoral research associate to conduct both theoretical and applied research in the areas of computer vision and machine learning. Specific areas of interest include (but not limited to):

  • Human pose/motion estimation, activity recognition, human body shape modeling, sports analytics/ergonomics, performance/injury prediction, and other human factors areas
  • Computer graphics, geometric deep learning, graph neural networks, statistical shape analysis, 3D reconstruction, and other digital geometry processing applications
  • Scientific machine learning (SciML), data-driven modeling of dynamic processes, uncertainty quantification, stochastic process modeling
  • Federated learning, distributed machine learning, and distributed big data systems

Successful candidates will participate in one or more of relevant research projects sponsored by the federal government/industry partners, including the National Science Foundation, National Institutes of Health, U.S. Department of Defense, etc. Responsibilities will include conducting cutting-edge scientific research, designing novel mathematical formulae and algorithms, communicating research findings through scientific publications, developing and maintaining reproduceable software codes, and mentoring graduate students.

Successful candidates may also participate in teaching and other expanded duties if they are interested in building broader career experience.

Qualifications

  • A doctoral degree in data science, computer science/engineering, applied mathematics, or other relevant areas by the start date of the position.
  • Strong verbal/written communication skills
  • Publication record in top-tier journals/conferences
  • Proficiency in TensorFlow, PyTorch, MxNet, or other deep learning frameworks
  • Strong programming skills

This is a one-year term limited position with the possibility of renewal based on funding and satisfactory performance.


Selected candidates will be required to complete a background check prior to the first day of employment per the University policy.

Benefits include the opportunity to work in a highly multidisciplinary environment with a diverse team of researchers in data science, computer science, mechanical engineering, materials science, business analytics, medicine, and other disciplines. You will also have a chance to work with multi-institutional collaborators and to build a strong network. Competitive salary, insurance benefits, retirement funds, and other benefits will also be provided per the University policy.

To Apply

Complete an application online and attach:

  • Cover letter
  • CV
  • Three writing samples
  • Transcripts
  • Names and contact information of three referees

****Please combine all required application materials in the other listed above into one document and upload in the resume / cv box ***

PROCESS FOR INTERNAL UVA APPLICANTS : Please apply through your Workday Home page, search “Find Jobs”, and search for ‘R0029339’. Complete an application online and attach the required documents.

PROCESS FOR EXTERNAL UVA APPLICANTS : Please visit UVA job board https://uva.wd1.myworkdayjobs.com/UVAJobs , complete the application and attach the required documents.

For additional information about the position, please contact Stephen Baek at baek@virginia.edu

For information about the application process, please contact Rhiannon O’Coin at rmo2r@virginia.edu

About the School of Data Science

The University of Virginia has announced plans to establish a School of Data Science, an effort made possible in part by the largest private gift in the institution’s 200-year history. The School of Data Science – UVA’s 12th school and the first established since 2007 – will position the University as a global leader in efforts to improve society through teaching and research based on the powerful, emerging field of data science. It builds on a foundation set in place at UVA by the Data Science Institute (DSI), a pan-University institute established in 2013 that grants graduate degrees and has a dual mission in education and research.


COVID Vaccination Requirement
 

The University of Virginia expects all current and new employees (UVA Health System and Academic), to be vaccinated against COVID-19. 
 
If hired to work within the University Health System, you will be required to provide proof of vaccination or be willing to receive the vaccination. Employees may request a medical or religious exemption from vaccination.
 
If hired to work on the Academic side of the University, excluding the School of Medicine, School of Nursing, UPG, and the Health Systems Library, you will be required to provide proof of vaccination or be willing to submit to mandatory, weekly prevalence testing. Employees that are working 100% remotely will not be subject to weekly prevalence testing; however, if the employee works on UVA Grounds (including the Medical Center) even intermittently, then they are required to be tested for COVID-19 once per week on an indefinite basis and follow masking mandates. 
 
NOTE: Some medical and safety-sensitive positions require vaccination and are not eligible for an exemption.  For more information on how the vaccination and testing requirements will apply to you at your work location, see the UVA New Hire Vaccination Requirements webpage. 

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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