Computational Bioimaging Engineer

About the role

Arago Labs is looking for an engineer or scientist to lead the development of the computational imaging pipeline for its next-generation surgical endomicroscope. The successful candidate works independently, owning the process from raw detector signals to real-time reconstructed images, and takes a system from early development to a robust, working implementation.

Key responsibilities

• Design and implement the microscope's signal processing and image reconstruction pipeline.
• Develop algorithms for signal recovery, noise reduction, image reconstruction and image quality improvement.
• Implement and optimize algorithms for real-time execution, including CPU and GPU acceleration where appropriate.
• Integrate reconstruction software with detector electronics, data acquisition hardware and microscope control systems.
• Develop methods for calibration, synchronization and correction of hardware-related signal artifacts.
• Evaluate and optimize imaging performance in terms of reconstruction quality, throughput, computational efficiency and latency.
• Design reliable, modular and maintainable software suitable for a medical imaging system.
• Work with the team to translate hardware capabilities into computational imaging solutions and take technical ownership of the subsystem, from requirements and architecture to testing and validation.

Required profile

• MSc or PhD in electrical engineering, computer science, physics, computational imaging or a related field, or equivalent industry experience.
• Strong background in digital signal processing, computational imaging, numerical methods or image reconstruction.
• Ability to independently develop algorithms, evaluate alternatives and make well-founded technical decisions.
• Comfortable working independently in an interdisciplinary, unstructured startup environment.

Required skills

• Excellent programming skills in Python and C++, able to turn research algorithms into production-quality code.
• Experience with performance optimization, parallel processing or GPU programming, preferably with CUDA.
• Experience with raw measurement data from imaging systems, sensors or scientific instruments.
• Nice to have: optical imaging, laser scanning or fluorescence microscopy; low-photon-count imaging; real-time, low-latency pipelines and streaming data; FPGA or embedded systems integration; knowledge of inverse problems, model-based reconstruction, computational optics or machine learning for image restoration; experience with medical device software.