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Research & Development 🏢 Full Time ⭐️ Verified

Senior Research Scientist

Nexus Innovations
San Francisco
Salary Estimate
USD 180.000 – USD 220.000
Live Update
25 Mei 2026
Deadline
25 Mei 2027

Job Description

Join Nexus Innovations' elite Research & Development division at the forefront of technological breakthroughs. We're pioneering next-generation AI solutions that redefine human-machine interaction. As a Senior Research Scientist, you'll lead transformative projects in machine learning, quantum computing, and bioinformatics. Our state-of-the-art labs in San Francisco provide unparalleled resources for experimentation and collaboration. Enjoy competitive compensation, flexible work arrangements, and the opportunity to shape the future of technology.

Responsibilities

  • Lead multidisciplinary R&D projects in artificial intelligence and computational biology
  • Design and conduct advanced experiments to validate novel hypotheses
  • Collaborate with engineering teams to translate research into scalable solutions
  • Secure federal and private funding through grant proposals and patents
  • Mentor junior researchers and publish findings in top-tier journals
  • Stay current with emerging technologies through industry conferences
  • Contribute to intellectual property strategy and portfolio development

Qualifications

  • PhD in Computer Science, Physics, or related quantitative field
  • 5+ years of industry research experience with demonstrated publications
  • Expertise in Python, TensorFlow/PyTorch, and high-performance computing
  • Strong background in statistical modeling and experimental design
  • Proven track record of securing research funding
  • Experience with cloud platforms (AWS/GCP) and containerization
  • Excellent communication skills for technical and non-technical audiences
  • Ability to thrive in ambiguous, fast-paced innovation environments

Required Skills

Machine Learning Quantum Computing Data Science Experimental Design Patent Development High-Performance Computing Statistical Modeling AWS/GCP

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