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Machine Learning Biomedical Engineer Jobs in Connecticut

Varsity Tutors

Biomedical Engineering Tutor

Norwalk, CT · Remote

$40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for online Biomedical Engineering tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have ...

Varsity Tutors

Biomedical Engineering Tutor

Stamford, CT · Remote

$40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for online Biomedical Engineering tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have ...

Varsity Tutors

Biomedical Engineering Tutor

Hartford, CT · Remote

$40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for online Biomedical Engineering tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have ...

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Machine Learning Biomedical Engineer information

What are the key skills and qualifications needed to thrive as a Machine Learning Biomedical Engineer, and why are they important?

To thrive as a Machine Learning Biomedical Engineer, you need a strong background in biomedical engineering, data analysis, and machine learning, typically supported by a degree in biomedical engineering, computer science, or a related field. Familiarity with programming languages like Python or R, machine learning frameworks (e.g., TensorFlow, PyTorch), and experience with medical imaging or signal processing tools are commonly required. Critical thinking, problem-solving, and the ability to communicate complex technical concepts to interdisciplinary teams are vital soft skills. These abilities are crucial for developing innovative healthcare solutions, ensuring regulatory compliance, and bridging the gap between technology and medicine.

How does a Machine Learning Biomedical Engineer typically collaborate with clinicians and researchers in a healthcare setting?

Machine Learning Biomedical Engineers often work closely with clinicians and researchers to develop algorithms that solve real-world medical challenges. Collaboration usually involves understanding clinical needs, translating them into technical requirements, and iteratively refining models based on feedback from medical experts. Regular meetings, interdisciplinary project teams, and direct participation in data collection or validation studies are common. This collaborative environment ensures that technical solutions are both innovative and clinically relevant, making communication and adaptability essential skills.

What does a Machine Learning Biomedical Engineer do?

A Machine Learning Biomedical Engineer applies machine learning techniques to solve problems in biology and medicine. They develop algorithms and models to analyze complex biomedical data, such as medical images, genetic information, or sensor readings. Their work supports advancements in diagnostics, treatment planning, and personalized medicine. Typically, they collaborate with clinicians, researchers, and other engineers to design systems that improve healthcare outcomes.

What is the difference between Machine Learning Biomedical Engineer vs Data Scientist in Biomedical Industry?

AspectMachine Learning Biomedical EngineerData Scientist in Biomedical Industry
Required CredentialsDegree in Biomedical Engineering, Computer Science, or related fields; knowledge of machine learning and biomedical dataDegree in Data Science, Statistics, or related fields; proficiency in data analysis and machine learning
Work EnvironmentResearch labs, healthcare institutions, biotech companiesHealthcare analytics firms, research institutions, biotech companies
Employer & Industry UsageDevelops algorithms for medical devices, diagnostics, and treatment planningAnalyzes biomedical data to inform clinical decisions, research, and product development

Both roles require expertise in machine learning and biomedical data, but Machine Learning Biomedical Engineers focus on developing algorithms for medical applications, while Data Scientists analyze biomedical data to support research and clinical decisions.

What are popular job titles related to Machine Learning Biomedical Engineer jobs in Connecticut? For Machine Learning Biomedical Engineer jobs in Connecticut, the most frequently searched job titles are:
What job categories do people searching Machine Learning Biomedical Engineer jobs in Connecticut look for? The top searched job categories for Machine Learning Biomedical Engineer jobs in Connecticut are:
What cities in Connecticut are hiring for Machine Learning Biomedical Engineer jobs? Cities in Connecticut with the most Machine Learning Biomedical Engineer job openings:
Machine Learning Biomedical Engineer jobs near you
Computational Image Analysis Scientist - 2D/3D Biomedical Imaging

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

Astrix Inc

Ridgefield, CT • On-site

$39 - $42/hr

Contractor

Posted 11 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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