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Internship Computational Imaging Scientist Jobs (NOW HIRING)

Apple

Image Scientist - Camera Simulation

Cupertino, CA · On-site

The Image Sciences team, a part of the Camera Hardware and Depth Team, develops novel metrology ... Optics: imaging system design, Computer Vision, computational imaging, or similar. Experience with ...

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Internship Computational Imaging Scientist information

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$50.5K

$111.3K

$137.5K

How much do internship computational imaging scientist jobs pay per year?

As of Aug 8, 2026, the average yearly pay for internship computational imaging scientist in the United States is $111,343.00, according to ZipRecruiter salary data. Most workers in this role earn between $94,500.00 and $137,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an internship computational imaging scientist, and why are they important?

To thrive as an Internship Computational Imaging Scientist, you typically need a background in computer science, electrical engineering, or a related field with knowledge of image processing, algorithms, and mathematics. Familiarity with programming languages such as Python or MATLAB, and experience using libraries like OpenCV or TensorFlow, are commonly required, along with coursework or certifications in computational imaging. Strong problem-solving skills, attention to detail, and the ability to communicate technical findings effectively are important soft skills. These competencies enable effective development, analysis, and communication of imaging solutions within research or industry teams.

What does an internship computational imaging scientist do?

An Internship Computational Imaging Scientist assists in developing and applying advanced computational techniques to process and analyze images. This role often involves working with large datasets, using programming languages like Python or MATLAB, and collaborating with senior scientists to solve imaging problems in fields such as biomedical imaging, computer vision, or microscopy. Interns may help design algorithms, conduct experiments, and interpret results to support new imaging technologies. The position offers hands-on experience in both research and practical applications of computational imaging.

What types of projects does an internship computational imaging scientist typically work on, and how do these projects contribute to larger team goals?

As an Internship Computational Imaging Scientist, you’ll often work on projects such as developing new image processing algorithms, optimizing data acquisition techniques, or assisting in the design of computational pipelines for imaging applications. These projects are usually part of broader research or product development efforts and directly support the team’s goals of advancing imaging technology and providing actionable insights from complex data. You’ll frequently collaborate with senior scientists, engineers, and sometimes clinicians or product managers, gaining exposure to multidisciplinary teamwork and real-world problem-solving.

What is the difference between Internship Computational Imaging Scientist vs Research Scientist in Computational Imaging?

AspectInternship Computational Imaging ScientistResearch Scientist in Computational Imaging
CredentialsEnrolled in or recent graduate of relevant degree (e.g., computer science, engineering)Advanced degree (Master's or PhD) often preferred
Work EnvironmentInternship programs, collaborative research labs, industry or academiaFull-time research roles in academia, industry, or research institutions
Employer & Industry UsageTech companies, startups, research labs focusing on imaging techUniversities, research institutes, industry R&D departments
Search & Comparison IntentEntry-level, learning-focused roles, internshipsAdvanced research, development, and innovation roles

The main difference is that an Internship Computational Imaging Scientist is an entry-level, temporary position aimed at gaining experience, while a Research Scientist in Computational Imaging is a full-time, often advanced role focused on conducting independent research and development in the field.

More about Internship Computational Imaging Scientist jobs
What cities are hiring for Internship Computational Imaging Scientist jobs? Cities with the most Internship Computational Imaging Scientist job openings:
What are the most commonly searched types of Computational Imaging Scientist jobs? The most popular types of Computational Imaging Scientist jobs are:
What states have the most Internship Computational Imaging Scientist jobs? States with the most job openings for Internship Computational Imaging Scientist jobs include:
What job categories do people searching Internship Computational Imaging Scientist jobs look for? The top searched job categories for Internship Computational Imaging Scientist jobs are:
Internship Computational Imaging Scientist jobs near you
Infographic showing various Internship Computational Imaging Scientist job openings in the United States as of August 2026, with employment types broken down into 4% As Needed, 69% Full Time, 14% Part Time, and 13% Contract. Highlights an 95% Physical, 1% Hybrid, and 4% Remote job distribution, with an average salary of $111,343 per year, or $53.5 per hour.

Computational Image Analysis Scientist - 2D/3D Biomedical Imaging

Astrix Inc

Ridgefield, CT • On-site

$39 - $42/hr

Contractor

Re-posted 21 days ago

Job description

Our client is a global, research-driven pharmaceutical manufacturer focusing on treatment options for diseases and conditions for which there is no satisfactory treatment option to date. The company is looking for a Computational Image Analysis Scientist - 2D/3D Biomedical Imaging to join the team. This is an amazing opportunity to work on cutting edge treatments and make a difference!
Job Title: Computational Image Analysis Scientist - 2D/3D Biomedical Imaging
Pay rate: $39/hr.- $42/hr.
Location: Ridgefield, CT
Job type: 2-year contract
Position Summary
We are seeking a Computational Image Analysis Scientist to develop, optimize, and apply advanced image analysis workflows for 2D and 3D biomedical imaging data. The role focuses on quantitative analysis of histology, immunohistochemistry (IHC), immunofluorescence (IF), and multiplex imaging datasets to support biomarker discovery, translational research, and preclinical/clinical studies.
The ideal candidate combines strong programming and machine learning expertise with hands-on experience in digital pathology and a collaborative mindset for working with multidisciplinary scientific teams.
Key Responsibilities
  • Develop, implement, and optimize image analysis pipelines for 2D and 3D biomedical imaging datasets
  • Perform quantitative analysis of histology, IHC, IF, and multiplex imaging (mIF) data
  • Apply classical image processing and machine learning methods for:
    • Image segmentation
    • Feature extraction
    • Cell detection and classification
  • Analyze and quantify spatial biology and cellular phenotypes from tissue imaging data
  • Integrate and work across digital pathology platforms including:
    • HALO AI
    • Visiopharm
    • QuPath
    • CellProfiler
  • Collaborate closely with pathologists, biologists, and data scientists to define analytical endpoints and experimental design
  • Validate image-derived biomarkers and ensure scientific and analytical rigor
  • Document workflows to ensure reproducibility and regulatory-grade traceability
  • Support interpretation, visualization, and presentation of imaging-derived data for scientific reports and publications
  • Enable cross-lab collaboration through transfer of image analysis workflows and algorithms

Required Qualifications
  • Bachelor's degree with 3+ years of experience, or Master's degree in a relevant scientific discipline (or equivalent experience)
  • Strong proficiency in Python and/or R for scientific computing and data analysis
  • Demonstrated experience in machine learning applied to image data
  • Hands-on experience with digital pathology or biomedical image analysis
  • Experience working with H&E, IHC, and multiplex immunofluorescence (mIF) datasets
  • Proven ability to perform cell segmentation, classification, and marker quantification
  • Experience using at least one digital pathology or image analysis platform (e.g., HALO, Visiopharm, QuPath, CellProfiler)
  • Strong problem-solving skills and ability to work independently in a research-driven environment

Preferred Qualifications
  • Experience in tumor immunology, histopathology, or spatial biology
  • Prior experience in biotech, pharmaceutical, or industry research environments
  • Familiarity with advanced spatial or multiplex imaging technologies

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