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Virtual Scientific Computing Jobs (NOW HIRING)

$150 - $200/hr

In Person/Virtual - TBD Full-time | Novato or Petaluma, CA QT Imaging is a medical device company ... Strong programming experience in Python, MATLAB, C++, or similar scientific computing languages and ...

$201K/yr

POSITION SPECIFICS We are seeking a Research Computing Software Engineer to join the Visualization ... data science, artificial intelligence, simulation, knowledge communication and virtual ...

$80 - $100/hr

... Scientific Computing (SciComp) High-Performance Computing (HPC) environment. * Schedule, coordinate, and facilitate virtual technical training programs, including brown-bag sessions, workshops ...

... or virtual screening. * Experience working with biological data such as molecular structures, compounds, sequences, and databases. * Programming experience in Python and scientific computing ...

This role sits at the intersection of software engineering and scientific computing, working across ... This position offers a hybrid schedule, blending in-person and virtual presence. You will have the ...

Python Software Developer

Livermore, CA · On-site

$59 - $81.25/hr

This role sits at the intersection of software engineering and scientific computing, working across ... This position offers a hybrid schedule, blending in-person and virtual presence. You will have the ...

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How much do virtual scientific computing jobs pay per week?

As of Sep 8, 2026, the average weekly pay for virtual scientific computing in the United States is $1,389.29, according to ZipRecruiter salary data. Most workers in this role earn between $1,163.46 and $1,471.15 per week, depending on experience, location, and employer.

What is virtual scientific computing?

Virtual scientific computing refers to the use of cloud-based or remote computational resources to perform scientific research and analysis. Instead of relying solely on local hardware, scientists access high-performance computing environments, data storage, and specialized software through the internet. This approach enables greater flexibility, scalability, and collaboration, allowing researchers to run complex simulations, analyze large datasets, and share results with colleagues worldwide. Virtual scientific computing is widely used in fields such as physics, chemistry, biology, and engineering.

What are the key skills and qualifications needed to thrive in virtual scientific computing?

To thrive in Virtual Scientific Computing, you need a solid background in mathematics, programming (often Python, C++, or MATLAB), and computational science, typically supported by a relevant degree. Familiarity with high-performance computing (HPC) environments, cloud computing platforms, and simulation software is commonly required. Strong analytical thinking, problem-solving ability, and effective collaboration are vital soft skills for excelling in multidisciplinary teams. These competencies are crucial for efficiently solving complex scientific problems and advancing research using computational methods.

What are some typical challenges faced by professionals in virtual scientific computing roles, and how can they be addressed?

Professionals in Virtual Scientific Computing often encounter challenges such as managing large-scale simulations, ensuring computational accuracy, and optimizing performance across diverse hardware architectures. Collaborating effectively with multidisciplinary teams—such as scientists, engineers, and IT specialists—can also be complex due to varying technical backgrounds. Addressing these challenges usually involves continuous learning, leveraging robust collaboration tools, and staying updated on the latest computational methods and best practices to ensure efficient and accurate results.
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Infographic showing various Virtual Scientific Computing job openings in the United States as of September 2026, with employment types broken down into 87% Full Time, 10% Part Time, and 3% Contract. Highlights an 45% Physical, 2% Hybrid, and 53% Remote job distribution, with an average salary of $72,243 per year, or $34.7 per hour.

Scientific Computing Research Engineer

On-site

QT Imaging, Inc.
11 - 50 employees

$150 - $200/hr

Other

Posted 19 days ago


Key responsibilities

  • Develop computational models and simulations of QT Imaging's Breast Acoustic CT™ technology.

  • Design and execute quantitative analyses of clinical imaging datasets.

  • Support clinical study design, endpoint development, statistical analysis plans, and interpretation of study results.


Job description

In Person/Virtual - TBD Full-time | Novato or Petaluma, CA

QT Imaging is a medical device company engaged in research, development, and commercialization of innovative body imaging systems using low frequency sound waves. QT Imaging strives to improve global health outcomes. Its strategy is predicated upon the fact that medical imaging is critical to the detection, diagnosis, and treatment of disease and that it should be safe, affordable, accessible, and centered on the patient’s experience. For more information on QT Imaging, please visit the company’s website at www.qtimaging.com

Job Description Overview

This position primarily supports QT Imaging’s scientific and clinical development programs through computational modeling, quantitative image analysis, and statistical evaluation of clinical data. Working directly with the Chief Science Officer, the successful candidate will develop simulation tools, analyze imaging datasets, evaluate algorithm performance, and support the design and execution of clinical studies.

The role bridges engineering, physics, computer science, and clinical research, providing quantitative analyses that support product development, regulatory submissions, scientific publications, and future AI development.

[Reports to: Chief Science Officer]

Key Responsibilities

  • Develop computational models and simulations of QT Imaging’s Breast Acoustic CT™ technology.
  • Design and execute quantitative analyses of clinical imaging datasets.
  • Process and analyze large multimodal imaging datasets, including QTscan, MRI, mammography, ultrasound, and pathology data.
  • Evaluate image quality, quantitative biomarkers, segmentation algorithms, and reconstruction performance.
    • Develop software tools for data processing, visualization, statistical analysis, and scientific reporting.
  • Support clinical study design, endpoint development, statistical analysis plans, and interpretation of study results.
  • Perform validation studies comparing QTscan with existing breast imaging modalities.
  • Work closely with Clinical Affairs, Engineering, Regulatory Affairs, and Software Development teams.
  • Prepare scientific reports, abstracts, conference presentations, regulatory documentation, and peer-reviewed publications.
  • Support development and validation of AI and machine learning algorithms using high-quality clinical datasets.
  • Provide quantitative correlation analyses of scanner test data to image reconstruction images.
  • Contribute to scientific publications, grant applications, and intellectual property development.
  • Assist in developing computational workflows that improve efficiency and reproducibility of scientific analyses.

Prior Experience

Qualifications & Requirements

  • S. or Ph.D. in Biomedical Engineering, Medical Physics, Electrical Engineering, Computer Science, Applied Mathematics, Biomedical Data Science, Physics, or a related field.
  • Strong programming experience in Python, MATLAB, C++, or similar scientific computing languages and use of Linux operating system.
  • Experience with image processing, signal processing, computer vision, or computational modeling.
  • Experience analyzing large clinical or imaging datasets.
  • Familiarity with medical imaging modalities such as MRI, CT, ultrasound, PET, or optical imaging.
  • Understanding of statistical analysis, experimental design, and clinical research methodology.
  • Experience working with DICOM imaging data.
  • Knowledge of machine learning and artificial intelligence methodologies is desirable.
  • Ability to work independently in a fast-paced, multidisciplinary environment.
  • Excellent written and verbal communication skills.
  • Experience with breast imaging is highly desirable.
  • Strong problem-solving and analytical skills to identify and resolve production issues
  • Experience with scientific visualization and data analysis libraries (NumPy, SciPy, Pandas, OpenCV, ITK, VTK, TensorFlow, or PyTorch).
  • Familiarity with Linux environments and high-performance computing
  • Experience supporting FDA-regulated medical device development is preferred.
  • Experience contributing to scientific publications and conference presentations.
  • Knowledge of ISO 13485 and Design Control processes is beneficial.
  • Strong analytical, organizational, and problem-solving skills.
  • Comfortable working collaboratively with physicians, scientists, software engineers, and regulatory teams.

Salary Range

Job Type

Location

This job description is a summary of the typical functions of the position, not necessarily an exhaustive or comprehensive list of all possible position responsibilities, tasks, and duties. The company reserves the right to assign or reassign duties and responsibilities to this job at any time. This job does not constitute a written or implied contract of employment; employment remains “at-will”.

Interested in learning more about our Quantitative Transmission Imaging Technology or about the QTI Breast Acoustic CT™ Scanner?QT Imaging Holdings, Inc.

Three Hamilton Landing, Suite 160

Novato, CA 94949

+1 (415) 842-7250

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