The postdoctoral researcher should bring a strong background in Artificial Intelligence (AI) to contribute to innovative projects at the intersection of AI and healthcare/medicine. The ideal candidate will have substantial experience applying AI technologies in medical and healthcare settings, demonstrating a proven track record through several relevant publications in the field. This is an exciting opportunity for a motivated professional to work on cutting- edge AI solutions that have the potential to transform healthcare delivery and outcomes.

Major Responsibilities

Lead and contribute to the development of AI models and algorithms specifically designed for healthcare applications, including diagnostics, medical imaging, personalized medicine, and patient care optimization.

Collaborate with interdisciplinary teams of medical professionals, data scientists, and biostatisticians to integrate AI technologies into existing healthcare systems and clinical workflows.

Design and execute research projects that aim to explore innovative uses of AI in medicine, ensuring that outcomes are documented and published in high-impact, peer-reviewed journals.

Analyze complex healthcare data sets, including electronic health records (EHRs), imaging data, and genomic/epigenomic information, to develop predictive models and actionable insights.

Provide technical guidance and mentorship to junior researchers and team members on the application of AI in healthcare.

Maintain knowledge of the latest advancements in AI, machine learning, and deep learning technologies, and assess their potential applications in medical contexts.

Present research findings and project progress to stakeholders, including senior leadership and external partners, in a clear and effective manner.

A strong publication record in AI and healthcare-related topics.

Proven experience in developing and deploying AI models in clinical or medical research settings.

Proficiency with programming languages such as Python, R, or similar, and experience with AI/ML frameworks such as TensorFlow, PyTorch, or Keras.

Knowledge of healthcare data systems, including EHRs, and an understanding of regulatory and privacy considerations in healthcare (e.g., HIPAA compliance).

Strong analytical, problem-solving, and communication skills, with the ability to work effectively in an interdisciplinary team environment.

Demonstrated ability to manage projects, meet deadlines, and produce high-quality research outputs.