SRI/PARC is offering a Research Internship opportunity in the areas of 3D image segmentation, machine learning, artificial intelligence, and human-in-the-loop methodologies, with a focus on practical skills. The candidate will have the opportunity to work with single-cell soft X-ray tomographic data produced at the National Center for X-ray Tomography (https://ncxt.org/; Lawrence Berkeley National Laboratory). They will gain experience in interpreting large biological tomographic images and develop semi-automatic methods to segment biological images with limited 3D features. Exceptional graduate students with hands-on experience in these fields are encouraged to apply.

• Develop and implement machine learning algorithms for 3D image segmentation, incorporating human-in-the-loop methodologies.
• Develop high-quality and scalable code according to industry standards.
• Contribute to conference or journal papers in the field of 3D image segmentation and machine learning, with an emphasis on human-in-the-loop techniques.

• Current graduate student majoring in Computer Science, Software/Computer/Electrical Engineering, Applied Math, or related discipline
• Demonstrable excellence in at least one high-level programming language (e.g., Python or C/C++, not notebooks); willingness to develop according to industry standards (development for deployment, clean and collaborative coding, git usage, unit testing, etc.)
• Eagerness to learn new technologies, apply practical techniques to solve real-world problems, and develop new ideas into software products.
• Up-to-date knowledge of machine learning, deep learning, and various neural network models and their pros and cons for different applications, particularly in the context of 3D image segmentation and human-in-the-loop methodologies.
• Outstanding written and oral communication skills.

Preferred Skills:

• At least one year of academic research experience focusing on 3D image segmentation, machine learning, and human-in-the-loop techniques.
• Experience using napari for visualization and annotation of multi-dimensional image data.
• Familiarity with popular deep learning frameworks, such as TensorFlow or PyTorch, and libraries for image processing, such as OpenCV or scikit-image.
• Strong problem-solving skills and the ability to work independently or collaboratively within a team.
• Knowledge of best practices in human-computer interaction, user experience, and/or user interface design for incorporating human feedback into segmentation tasks.

The salary range is: $30-$36/hr. Salary ranges will vary and are based on several factors, including geographic location, market competitiveness and equity amongst internal employees in similar roles. Positions may also qualify for SRI's Pay for Outstanding Performance program or the annual Performance Based Compensation program. SRI also has a competitive benefits package, to view details please go to https://www.sri.com/resources/benefits/.

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