Responsibilities

• Design and implement machine learning algorithms for analyzing medical video images captured by our proprietary spectroscopy-based microscope.
• Research and integrate state-of-the-art methods in computer vision and image analysis (both deep and classical methods) to enhance the accuracy and efficiency of ML models.
• Develop and maintain scalable data processing pipelines and model deployment workflows.
• Enable the work of large-scale clinical trial data to support the development and validation of predictive blood count models.
• Collaborate closely with physicists, software engineers and HW engineers in a fast-paced, multidisciplinary environment.

Qualifications

• MSc or PhD in Computer Science, Electrical Engineering

  or a related field.

• A top performer with at least 5 years of hands-on, post-academic experience in developing deep learning and computer vision algorithms.

• Ability to lead algorithm development from ideation through implementation, including experimental design, iterative development, and performance evaluation.

• Expertise in classical computer vision methods and modern deep learning frameworks such as PyTorch and numerical libraries such as numpy and scikit-learn.

• Excellent problem-solving skills, critical thinking, and the ability to work both independently and collaboratively in a multidisciplinary team.

• Experience working with medical or biological data is an advantage.