• Develop, implement, and optimize LLMs and computer vision algorithms for processing and analyzing biomedical text and image data.
• Design and develop software tools and pipelines for automated image analysis, data integration, and visualization, leveraging machine learning and deep learning techniques.
• Collaborate with biologists and other researchers to understand their needs and translate them into technical solutions, incorporating state-of-the-art AI methodologies.
• Perform data mining, statistical analysis, and machine learning on large-scale biomedical imaging datasets to extract meaningful insights and improve predictive accuracy.
• Validate and benchmark AI-driven imaging algorithms and tools to ensure their accuracy, robustness, and scalability.
• Document software development processes, create user manuals, and provide training and support to end-users, particularly focusing on AI applications.
• Stay up-to-date with the latest advancements in AI, computer vision, biomedical imaging, computational biology, and data science, and apply this knowledge to improve existing tools and methodologies.
• Participate in interdisciplinary team meetings, present findings, and contribute to scientific publications and grant proposals, emphasizing AI and computer vision innovations.
• Identify and implement new AI technologies and frameworks to enhance the capabilities of biomedical imaging tools and methodologies.
• Knowledge of code packaging, containerization technologies, and continuous integration pipelines.
• DevOps experience with Kubernetes and workflow automation is a plus

Qualifications

• Ph.D. or Master’s degree in Data Science, Computer Science, Biomedical Engineering, Bioinformatics, or a related field.
• Proven experience in biomedical imaging analysis, AI, and computer vision, preferably in HTS and HCS contexts.
• Strong programming skills in languages such as Python. C++ and Rust is a plus.
• Well versed with AI and machine learning frameworks and libraries such as TensorFlow, PyTorch, PydanticAI, and LLM observability.
• Experience with image analysis software and libraries such as ImageJ, CellProfiler, OpenCV, or similar.
• Knowledge of statistical analysis and data visualization techniques.
• Familiarity with high-performance computing and cloud-based data processing environments.
• Excellent problem-solving skills and the ability to work both independently and as part of a team.
• Strong communication skills and the ability to convey complex technical concepts to non-technical audiences.
• Experience in developing AI-driven software tools for biomedical research.
• Experience with version control systems such as Git.
• Experience with workflow automation tools.
• Previous experience working in a collaborative, interdisciplinary research environment.