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Science Intern (Summer)

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Date: Oct 13, 2021

Location: San Francisco, US

Company: Dolby Laboratories, Inc.

Join the leader in entertainment innovation and help us design the future. At Dolby, science meets art, and high tech means more than computer code. As a member of the Dolby team, you’ll see and hear the results of your work everywhere, from movie theaters to smartphones.

 

As an intern, the Dolby U program offers impactful, project-based work experience in a collaborative, creative environment where you work side by side with industry leaders. Amplify your insatiable curiosity by implementing real-world solutions that revolutionize how people communicate and how entertainment is created, delivered, and enjoyed worldwide. For anyone seeking to gain invaluable expertise through meaningful, personal contributions, join us to design a future where technology meets entertainment!

 

SUMMARY

Dolby Laboratories is looking for a self-motivated, talented individual interested in applying their theoretical and practical expertise in the context of computational/data-driven development of innovative audio-visual technologies. This internship role will work closely with a scientific research and development team to develop, evaluate and integrate cross-platform technology solutions within entertainment, consumer electronics and communications ecosystems. The successful candidate will partner directly with other scientists, developers, and a data collection team to innovate solutions that optimize the human sensory experience. The position is in the Science Group–within the Technology Strategy department of Dolby Laboratories. It will involve work in close collaboration with team members in multiple locations.   

 

QUALIFICATIONS:

  • Strong interest in learning and researching new technologies Interest or experience in the study of sensory perception and application to technology development and assessment
  • Proficient in established/novel methods of experimental design and scientific hypothesis testing
  • Highly proficient in Python and/or Matlab
  • Experience with a variety of statistical analysis and machine learning methods
  • Proficient at writing technical papers/reports/presentations
  • Excellent abilities to work with new scientific problems regarding experimental design and applied development regardless of prior exposure to current topic
  • Excellent written and verbal communication skills Experience working in teams and a team-oriented work ethic   

 

DESIRED/PREFERRED QUALIFICATIONS

  • Exposure, and prior use of non-invasive human physiological measures such as EEG, galvanic-skin conductance, eye-tracking or other categorically similar methodologies
  • Experience designing or training neural networks for audio and/or video applications, using PyTorch, TensorFlow or similar frameworks.
  • Knowledge of signal processing theory
  • Experience with speech, audio, or video bit-rate reduction technologies
  • Experience working with quantitative methods of neural data analysis Interest or experience in the bimodal perception of audio-visual material
  • Critical listening or viewing skills   

 

ELIGIBILITY:

Working towards a B.Sc. or higher degree in Psychology, Neuroscience (Psychophysics), Computer Science or a related field; recent grads who are within 6 months of graduation are also eligible to apply Must be available to work full-time Monday–Friday for at least 3 months starting May/June 2022.

Start dates for the internship are as follows: (*note* these dates are not flexible)

  • Monday, May 23, 2022
  • Monday, June 6, 2022
  • Monday, June 20, 2022

 

Dolby will consider qualified applicants with criminal histories in a manner consistent with the requirements of San Francisco Police Code, Article 49, and Administrative Code, Article 12

 

Equal Employment Opportunity:
Dolby is proud to be an equal opportunity employer. Our success depends on the combined skills and talents of all our employees. We are committed to making employment decisions without regard to race, religious creed, color, age, sex, sexual orientation, gender identity, national origin, religion, marital status, family status, medical condition, disability, military service, pregnancy, childbirth and related medical conditions or any other classification protected by federal, state, and local laws and ordinances.