Careers

We make breakthrough discoveries happen. Join us!

We are seeking talented and passionate individuals to help us change the future of life sciences research, therapeutics, and diagnostics. We foster a collaborative, positive, and proactive culture, with opportunities to grow and lead in a dynamic environment.

Who are we? LifeCanvas is building pioneering technologies in volumetric tissue processing, light sheet imaging, and data analysis. By empowering researchers with unmatched tools and services for comprehensive molecular mapping, we are expediting drug discovery and development, disease model phenotyping, and precision medicine.

Why join us? We have an innovative product ecosystem and a global community of collaborators and technology adopters. You will be able to make an immediate impact on the future of biomedical research, working with world-class researchers in both academia and industry on bioengineering, drug discovery, oncology, and neuroscience projects.

Open roles

As a Research Associate, you will join a team of senior engineers, scientists, and computer scientists focused on developing and expanding our tissue processing and imaging product pipeline and providing high-quality 3D image data to customers via in-house operation of our flagship systems: SmartBatch+ and SmartSPIM.

Key responsibilities will include:

  • Benchwork and execution of state-of-the-art tissue processing systems, imaging, and artificial intelligence algorithms to quantify tissue image data
  • Providing comprehensive on-site installations, remote training & technical support for our end users to further the research efforts of world-class scientists in bioengineering, neuroscience, therapeutic discovery and related fields across the globe. (Travel may occasionally be required when necessary.)

Our ideal candidate will have:

  • Bachelor’s degree in engineering, or relevant biological sciences
  • A strong interest in working in a fast-growing life sciences start-up environment
  • Prior experience at the bench designing experiments and protocols (preferred)
  • Imaging experience (preferred)

Characteristics we are looking for:

  • You are energetic, adaptable, tenacious, and sincere
  • You want your work to have a positive impact
  • You are solution-oriented: enjoy solving problems and providing solutions
  • You communicate with clarity and can work in sync with the LifeCanvas team
  • You are about follow-through and delivery
  • You have a ‘no task too small’ attitude and impeccable work ethic
  • You are able to work under tight deadlines with exceptional attention to details

Featured benefits include:

  • Disability insurance

Summary

LifeCanvas Technologies, in collaboration with the Sorger Lab and Harvard Medical School, is seeking a postdoctoral fellow to join a two-year project focused on 3D tissue imaging, spatial biology, and AI-powered analysis.

What You Will Be Doing

LifeCanvas Technologies, in partnership with the Sorger Group and the Harvard Tissue Atlas Project in Harvard Medical School (HMS), is seeking a highly motivated and versatile postdoctoral fellow for a 2-year applied research position supported by the MLSC Bits to Bytes Research Award.

This unique opportunity places you at the intersection of industry and academia, where you will advance high-resolution 3D tissue imaging, spatial biology, and AI-driven data analysis in human tumor samples. You will contribute to development of cutting-edge image analysis algorithms (including machine learning/AI methods) and pipelines on large-scale datasets on clinically-relevant tissue samples.

This is an in-person position where you’ll be embedded in a hybrid environment between LifeCanvas (Cambridge, MA) and the Laboratory of Systems Pharmacology at HMS (Boston, MA), working on real-world challenges and building tools that translate into both scientific insight and practical applications. This role offers a unique opportunity to contribute to collaborative research while receiving mentorship from leaders in both biotech startup and academic spaces.

The ideal candidate is passionate about spatial biology, eager to work across disciplines, and excited to translate imaging and data innovations into biological and therapeutic discoveries.

Key Responsibilities

  • Develop AI/ML pipelines and image analysis workflows for large-scale clinical 3D tissue datasets generated with LifeCanvas platforms.
  • Collaborate with academic, industry, and clinical teams to design and execute joint projects.
  • Translate imaging findings into biologically and clinically relevant discoveries, including novel biomarkers and therapeutic targets.
  • Present work at conferences, contribute to publications, and help shape the development of new products and applications.
  • Serve as a scientific bridge between academic research and industry innovation.

Our Ideal Candidate Will Have

  • PhD in computer science, biomedical engineering, neuroscience, bioinformatics, or a related quantitative field.
  • Strong experience in machine learning, image analysis, and/or computational biology.
  • Proficiency in Python and libraries such as PyTorch, TensorFlow, scikit-image, or similar
  • A solid record of scientific contributions (e.g., publications, software tools, patents).
  • Ability to work independently in a fast-paced startup and academic environment while also thriving in interdisciplinary, collaborative settings.
  • Strong creative problem-solving skills.
  • Familiarity with tissue imaging (e.g., light sheet, confocal, or other high-resolution microscopy) or spatial omics techniques is a plus.

Characteristics We Are Looking For

  • Mission-focused, with a passion for translational research and technology development.
  • Curious, proactive, and adaptable, with strong analytical and problem-solving skills.
  • Team-oriented and communicative, with the ability to collaborate across academic and industry partners.
  • Committed to scientific rigor, innovation, and continuous learning.
  • Comfortable working in fast-paced environments and managing multiple priorities.

Benefits include: