jobs in Panasonic R&D Center Singapore

全职 R-D Engineer - Researcher – Video Coding - Standardization 工作, 薪水, Panasonic R&D Center Singapore 公司招聘中 - Ricebowl

R-D Engineer - Researcher – Video Coding - Standardization

Panasonic R&D Center Singapore

Undisclosed

Singapore

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工作地点

  • Singapore

职位描述

岗位职责

Fresh graduates and early-career engineers are encouraged to apply.


Responsibilities:

  • Research and develop advanced video coding, compression, and neural-network-assisted coding technologies.
  • Design, implement, and evaluate algorithms using software experimentation frameworks.
  • Investigate, implement, and optimize neural-network-assisted coding tools that improve coding efficiency, compression performance, visual quality, or video codec functionality.
  • Analyze technical papers, standards documents, and emerging technologies.
  • Present and defend technical proposals and participate in technical discussions with experts from industry and academia.
  • Contribute to international multimedia standardization activities and technical proposal development.
  • Collaborate with researchers, software engineers, IP specialists, and product teams across Panasonic's global R&D network.


Requirements:

Required Qualifications

  • Bachelor's, Master's, or PhD degree in Computer Science, Computer Engineering, Electrical/Electronics Engineering, Mathematics, or a related discipline.
  • Good programming skills in C/C++ and Python.
  • Strong analytical and problem-solving skills.
  • Interest in algorithms, signal processing, data compression, multimedia systems, or neural-network-assisted coding technologies.
  • Good written and verbal communication skills.
  • Ability to prepare clear technical reports, documentation, and presentation materials.
  • Self-motivated, proactive, and willing to learn new technologies.
  • Able to work independently as well as collaboratively in a team environment.


Preferred Qualifications

The following are advantageous but not mandatory:

  • Knowledge of video coding, data compression, signal processing, or multimedia systems.
  • Familiarity with machine learning or neural network frameworks.
  • Experience with neural network modification, tuning, training, or evaluation.
  • Experience with scripting, software experimentation, automation, or data analysis.
  • Experience preparing technical reports, research papers, patents, or project documentation.
  • Participation in engineering competitions, open-source projects, personal technical projects, or relevant research activities.

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