Data Scientist in AI Medical Imaging developing algorithms for improving ophthalmology diagnostics. Collaborating with cross-functional teams to integrate AI solutions into medical workflows.
Responsibilities
Develop and optimize machine learning algorithms for medical imaging applications to improve the accuracy and efficiency of ophthalmic diagnostics.
Collaborate with cross-functional teams, including software engineers and clinicians, to integrate AI solutions into existing medical workflows and tools.
Analyze large datasets from diverse sources to ensure data quality and integrity, and to train and validate AI models for detecting eye-related conditions.
Stay up to date with the latest developments in AI and medical technology, applying innovative approaches to improve products and patient outcomes.
Requirements
2+ years of practical industry experience in machine learning and deep learning, including working knowledge of CNNs, U-Net architectures, and standard ML techniques such as cross-validation and regularization.
4+ years of applied experience in computer vision and image analysis, including 2D/3D image processing, segmentation, and spatial normalization.
Strong programming skills in Python and experience with common machine learning frameworks such as PyTorch or TensorFlow.
Degree in Data Science, Computer Science, Bioengineering, (Medical) Physics, or a related quantitative field.
Experience working interdisciplinarily with physicians, data scientists, data engineers, and software engineers.
Experience analyzing and querying data using relational databases such as PostgreSQL.
Interest in extending clinical AI objectives to new areas such as diabetic macular edema (DME) or retinal vein occlusion (RVO).
Working proficiency in English (C1 level or higher).
Benefits
Direct impact on improving patients' quality of life by helping prevent blindness.
High level of ownership for your projects and opportunities for rapid professional growth.
Flexible working hours and remote work options.
Competitive compensation and a dynamic startup culture within a great international team.
Centrally located office in the Munich startup hub.
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