Postdoctoral Fellow, Computer Science

Location:
New Orleans, LA
Open Date:
Nov 17, 2022
Description:

A full-time postdoctoral position, up to two years renewable, is available in the Department of Computer Science at Tulane University, based in historic Uptown New Orleans. The postdoctoral researcher will work with Professor Peng’s group on one of the following areas:

  • Machine Learning Applications (on medical data, etc.)
  •  Deep Learning Accelerators
  •  Blockchain Applications (on healthcare, supply chain, etc.)
  •  Blockchain Accelerators
  •  Computer Architecture and High-Performance Computing
  •  Quantum Computer Architecture and Compiler

Qualifications:

Minimum Qualifications:

  • Ph.D. in computer science, computer engineering, electrical engineering, or a related area
  • Publications in IEEE / ACM conferences / journals.
  • Demonstrated research experience & programming skills

Application Instructions:

Candidates must apply via Interfolio and provide the following:

  • CV 
  • Research Statement
  • Transcript
  • Contact References (3)

Position will close on January 1, 2023, or when the position is filled.


Equal Employment Opportunity Statement:

Please Note: Tulane University has officially adopted a mandatory COVID-19 vaccination policy. All employees and visiting faculty must be fully vaccinated with a COVID-19 vaccination or obtain approval for a medical or religious exemption prior to beginning employment.

Tulane University is located in New Orleans - a city with tremendous history of diverse cultures, community, and languages. Tulane is actively building a campus culture grounded in our values of EDI and anti-racism. We seek and welcome candidate applications from historically underrepresented groups, such as BIPOC (Black, Indigenous, People of Color), women, LGBTQ+, and those living with disabilities as well as veterans. 

Tulane University is an Equal Employment Opportunity/Affirmative Action institution committed to excellence through diversity. Tulane University will not discriminate based upon race, ethnicity, color, sex, religion, national origin, age, disability, genetic information, sexual orientation, gender identity or expression, pregnancy, marital status, military or veteran status, or any other status or classification protected by federal, state, or local law. All eligible candidates are encouraged to apply.

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