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Biomedical Computer Vision Research Engineer

3 months ago


London, UK, United Kingdom Tech Kinect Full time
Job Responsibilities:
- Stay updated on the latest advancements in biomedical computer vision and effectively communicate these developments.
- Design and implement scalable, high-performance algorithms using advanced machine learning and neural network techniques on both on-premises and cloud-based distributed computing systems.
- Perform thorough data analysis and statistical modeling to refine and enhance models.
- Communicate results clearly and efficiently to both internal and external stakeholders through verbal and written reports.
- Develop high-quality, maintainable, and modular code with detailed documentation.

Job Requirements:
- Master’s or PhD degree, or equivalent experience, in applied mathematics, computer science, or a related quantitative field.
- Minimum of one year of experience in applying deep learning to biomedical imaging, evidenced by previous work, publications, open-source contributions, or participation in coding competitions.
- Experience working with histopathology data, including H&E-stained images or multi-/high-plex IHC data.
- Strong software engineering skills, with proficiency in Python, Linux, Git, and Docker.
- Extensive experience with machine learning frameworks, particularly PyTorch or JAX.
- Solid background in data science, including skills in data visualization, clustering, statistical testing, and regression/classification methods.
- Excellent English communication skills, both written and verbal.

Preferred Qualifications:
- Demonstrated research experience with publications in reputable journals.
- Experience with training foundational machine learning models.
- Familiarity with MLOps practices, including DevOps and CI/CD.
- Advanced knowledge in specialized computing areas, such as high-volume data storage and processing, high-performance computing, or deployment.
- Experience managing sensitive clinical data.
- Proven ability to mentor and guide colleagues.
- Experience transitioning machine learning research projects into production environments.