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San Carlos

    Imaging and Machine Learning Intern - San Carlos, California, United States - Noah Medical

    Noah Medical
    Noah Medical San Carlos, California, United States

    4 weeks ago

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    Description

    About The Team:

    Join the Imaging and Machine Learning Team at Noah Medical, where we are passionate about pioneering precision imaging guidance software and cutting-edge algorithms. Comprising seasoned engineers with advanced degrees and diverse expertise in medical imaging, machine learning, and healthcare applications, we are a dynamic group dedicated to innovation.

    Collaborating closely with clinical, product, and design teams, we have a strong focus on a user-centric approach to developing imaging solutions. Our collective mission is to revolutionize the landscape of healthcare through groundbreaking technology. We are on the lookout for individuals who are not only highly motivated but also possess a curious, independent spirit. If you're eager to tackle challenging problems, contribute to impactful medical imaging applications, and help foster a thriving work culture at Noah, we welcome you to join us in our pursuit of excellence.

    A Day In The Life Of Our Imaging and Machine Learning Intern (Segmentation):

    • Responsibilities of the job and what the individual will be doing on a day to day basis
    • Research, prototype, iterate algorithmic solutions to computer vision and deep learning problems to support image guided surgery.
    • Research current SOTA image segmentation algorithms/techniques, build functional software prototypes for automated lung anatomical segmentation.
    • Build ML data pipeline to power the algorithm development - organize training/testing data sets, organize and refine truth-labels and implement robust performance measures and evaluation strategies.
    • Perform extensive testing and evaluation of the algorithms and create documentation.
    • Explore the algorithm robustness w.r.t. different imaging scan parameters and different types of patients (e.g. normal vs abnormal).
    • Carry out investigation, research and development tasks as assigned.

    About You:

    • A passion in translating knowledge and concepts to real-life products that benefit the lives of people.
    • Preferably MS/PhD degree/candidacy in CS, EE, Biomedical Engineering or other related programs (exceptional BS will be considered too).
    • Strong implementation skills using Python.
    • GPU accelerated computing/CUDA experience will be a plus.Strong understanding of machine learning (ML) and deep learning fundamentals including data pipeline, models/architectures, training/evaluation process and deployment techniques.
    • Extensive training and hands-on experience in the following ML areas:
    • 2D/3D image segmentation, including algorithm development and evaluation.
    • Extensive experience working with PyTorch/Tensorflow.
    • Deep learning model optimization and deployment.
    • Experience in medical imaging is preferred, not a requirement.
    • Familiarity with tools such as OpenCV, ITK will be a plus.
    • Knowledge of version control tools like Git, SVN is preferred.
    • Solid foundation on mathematics and analytical skills, with the ability to quickly turn abstract conceptual ideas into working algorithm prototypes.
    • Being able to work full-time for at least 3 months.

    Workplace Type: Hybrid

    Benefits & Perks (For Full Time Employees):

    • Competitive Salary
    • Comprehensive health insurance including Medical, Dental and Vision + HSA and FSA options
    • Equity & Bonus Program
    • Life Insurance (company paid & supplemental) and Disability insurance
    • Mental health support through medical insurance programs
    • Legal and Pet Insurance
    • 12+ paid holidays, 15-20 days of PTO + use-what-you-need sick days
    • Paid parental leave
    • In-office snacks and beverages
    • In-office lunch stipend
    • Learning & Development Opportunities: On-demand online training and book reimbursement
    • Team building and company organized social and celebration events
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