[visionlist] Two open positions in Imaging Science at the Rochester Institute of Technology

[Gabriel Diaz]

We are currently recruiting for two open positions in Imaging Science at Rochester Institute of Technology.

The full posting is pasted below, but can also can be found here: https://sjobs.brassring.com/TGnewUI/Search/Home/Home?partnerid=25483&siteid=5291#jobDetails=1555577_5291

I have found RIT's Center for Imaging Science to be a wonderful place to work, and I'm excited at the possibility of attracting new colleagues working in vision science, or another field related to imaging.

 - gD

Gabriel J. Diaz, Ph.D.
Associate Professor
Director of PerForM Labs
Rochester Institute of Technology
Chester F. Carlson Center for Imaging Science

Office 2108, Building #76
Rochester, NY 14623
Office: (585) 475-6215
gabriel.diaz at rit.edu<mailto:gabriel.diaz at rit.edu>

____________

RIT Seeks Assistant Professor of Computer Vision - Computational Imaging – Machine Learning

The Chester F. Carlson Center for Imaging Science<https://www.rit.edu/science/chester-f-carlson-center-imaging-science> (CIS) at the Rochester Institute of Technology<https://www.rit.edu/> (RIT) invites candidates to apply for a tenure-track Assistant Professor of Imaging Science position. We are seeking two candidates with research expertise in computer vision, computational imaging, or machine learning, in the context of imaging systems and their applications.  Preference will be given to candidates whose research programs complement or extend the existing and well-established expertise within the Center, including remote sensing, optics, photonics, lasers, human vision, computer vision, machine learning, astronomy and space science, instrumentation, augmented and virtual reality, detectors, cultural heritage imaging, light-matter interactions, and nano-imaging.

The successful candidate will be expected to advise BS, MS and PhD students working across the imaging chain, teach undergraduate<https://www.rit.edu/science/study/imaging-science-bs> and graduate<https://www.rit.edu/science/study/imaging-science-phd> level courses in the core imaging science curriculum, offer elective courses in the candidate’s area of research, develop an externally funded research program, and live our values, embrace diverse perspectives, and nurture the RIT community to remain a great place to work for all.
Department/College Description
CIS is an interdisciplinary university research and academic unit dedicated to advancing the frontiers of imaging science and its technical applications, enabled by its robust research portfolio and degree programs. Imaging science is a diverse field which includes all aspects of the “imaging chain”, i.e., source-to-sensor radiometry, image acquisition, image processing, and interpretation by algorithms or people. With BS, MS, and PhD programs that focus on the physics of image formation, quantitative spectral and temporal image analysis, information extraction, image processing, computer vision, and the development and application of sensor and imaging instrumentation systems, the Center’s graduates are in high demand. At present, these programs comprise approximately 100 PhD students, 25 MS students, and 40 BS students. The Center’s 18 core tenure-track faculty, five research faculty, and 14 research scientists are responsible for annually attracting roughly $5M of research funding, derived from funding sources that include NSF, NIH, NASA, DoD, USDA, foundations, and industry. CIS faculty have extensive internal and external collaborations (industry and national labs), and contribute to or are affiliated with RIT’s PhD programs in color science, astrophysical sciences & technology, microsystems engineering, and computing & information sciences. For more information please see our annual report<https://www.rit.edu/science/sites/rit.edu.science/files/2021-07/CIS-AnnualReport2019-2020.pdf> and visit the CIS website<https://www.rit.edu/science/chester-f-carlson-center-imaging-science>.

Required Minimum Qualifications

  *   An earned doctoral degree (PhD or international equivalent) by the hire date (expected to be August 15, 2023).
  *   A record of refereed scholarly publications in a field related to imaging science that demonstrates expertise in computer vision, machine learning/deep learning, or computational imaging.
  *   An educational background or teaching history that demonstrates the ability to teach CIS core cources related to image processing, computer vision, or scientific computing.
  *   The ability to teach elective courses in their field of expertise at the undergraduate and graduate levels.
  *   Potential to obtain external research funding, as evidenced through an established track record via a cohestive research statement.
  *   Ability to communicate effectively.
  *   Ability to contribute in meaningful ways to the college’s continuing commitment to cultural diversity, pluralism, and individual differences.

Required Minimum Education Level PhD
Faculty Type (Tenure Status) Tenure-Track
Faculty Discipline Imaging Science, Machine Learning
Faculty Rank Assistant Professor
Employment Category Fulltime
Anticipated Start Date 16-Aug-2023

Required Application Documents
Cover Letter, Curriculum Vitae or Resume, List of References, Research Statement, Statement of Diversity Contribution, Statement of Teaching Philosophy
How To Apply
Apply online at http://careers.rit.edu/faculty  Keyword Search: 7359BR. Please submit your online application; curriculum vitae; a cover letter addressing the required qualifications, and upload the following atachments:

  *   Research statement
  *   Statement of teaching philosophy
  *   The names and email addresses for three references
  *   Contribution to Diversity Statement<https://www.rit.edu/academicaffairs/facultyrecruitment%20s/Diversity_Statement_Guide_for_candidates_4-12.docx>

Contact the search committee with questions on the position at jvacis at rit.edu. Review of applications will begin immediately and continue until a suitable candidate is found.  Application materials will be accepted through 1/17/2023.

Additional Details
The hiring process for this position may require a criminal background check and/or motor vehicle records check. Any verbal or written offer made is contingent on satisfactory results, as determined by Human Resources. RIT does not discriminate. RIT promotes and values diversity, pluralism and inclusion in the work place. RIT provides equal opportunity to all qualified individuals and does not discriminate on the basis of race, color, creed, age, marital status, sex, gender, religion, sexual orientation, gender identity, gender expression, national origin, veteran status or disability in its hiring, admissions, educational programs and activities. RIT provides reasonable accommodations to applicants with disabilities under the Rehabilitation Act, the Americans with Disabilities Act, the New York Human Rights Law, or similar applicable law. If you need reasonable accommodation for any part of the application and hiring process, please contact the Human Resources office at 585-475-2424 or email your request to hr at rit.edu. Determinations on requests for reasonable accommodation will be made on a case-by-case basis.
Commitment To Safety
COVID 19: Please familiarize yourself with the requirements of the RIT Safety Plan<https://www.rit.edu/ready/rit-safety-plan>. Information on the responsibility for each employee can be found on the RIT Ready<https://www.rit.edu/ready/> website. As per the RIT Employee COVID-19 Vaccination Policy<https://www.rit.edu/fa/humanresources/content/rit-mandatory-employee-covid-19-vaccination-policy>, all university employees must be fully vaccinated for COVID-19. Vaccination exemptions may be granted: (1) to employees who are unable to be vaccinated due to a medical condition or disability; (2) on the basis of an employee’s sincerely held religious belief, practice, or observance, or (3) to employees who are fully remote and sign an Employee Attestation stating that they will not be on campus for any reason, nor will they participate in any in-person university-sponsored activities.



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