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Senior Research Scientist, AI/ML, Imaging


PayCompetitive
LocationRedwood City/California
Employment typeFull-Time

This job is now closed

  • Job Description

      Req#: 7181892
      Employer Industry: Nonprofit Biomedical Research

      Why consider this job opportunity:
      - Salary up to $294,800
      - Opportunity for career advancement and growth within the organization
      - Hybrid work model requiring onsite presence for approximately 3 days a week
      - Generous employer match on 401(k) contributions
      - Annual benefits that can be tailored to individual needs, including support for housing, childcare, and student loan repayment
      - Paid time off for volunteering and funding for family-forming benefits

      What to Expect (Job Responsibilities):
      - Develop and apply advanced AI methods to address significant challenges in biological imaging
      - Work with diverse biological data types, including cell images and multi-omics data
      - Implement scalable solutions for complex scientific questions leveraging machine learning and statistical analysis
      - Collaborate with a team to utilize large open-source biological datasets for model development
      - Contribute to scientific literature through publications and presentations at conferences

      What is Required (Qualifications):
      - PhD or Master's in computer science, physics, applied math, or related field, or equivalent industry experience with at least 5 years in AI/ML methods
      - Experience in modern computer vision techniques, including vision transformers and diffusion models
      - Proven expertise in machine learning, including deep learning architecture design and data analysis
      - Hands-on experience with deep learning frameworks such as PyTorch or JAX
      - Strong communication and interpersonal skills, with the ability to work independently and collaboratively

      How to Stand Out (Preferred Qualifications):
      - Research and innovation experience in machine learning, computer vision, or computational biology, evidenced by publications or conference presentations
      - Familiarity with time series and longitudinal data analysis, representation learning, and geometric learning

      #NonprofitResearch #AI #MachineLearning #CareerGrowth #HybridWork #BiomedicalScience

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