About the job
We are looking for an innovative, collaborative Research Intern to join our efforts at the intersection of AI and healthcare, where we partner with premier medical centers and develop state-of-the-art deep learning, natural language processing (NLP), and multi-modal technologies to extract knowledge from tens of millions of research publications, distill patient information from hundreds of millions of electronic health records (EHRs), and assimilate them with billions of genomics data points to support biomedical research and clinical decision making.
Responsibilities
Conduct analyses using multimodal real-world data (RWD) sources such as electronic health records, medical imaging, and multi-omics to explore opportunities for modeling.
Collaborate with cross-functional teams to design and implement state-of-the-art systems by considering medical factors and responsible AI principles.
Propose novel approaches for unsolved research problems.
Qualifications
Minimum
Currently enrolled in a PhD program in Computer Science, or a related STEM field.
Other Requirements
Research Interns are expected to be physically located in their manager’s Microsoft worksite location for the duration of their internship.
In addition to the qualifications below, you’ll need to submit a minimum of two reference letters for this position as well as a cover letter and any relevant work or research samples. After you submit your application, a request for letters may be sent to your list of references on your behalf. Note that reference letters cannot be requested until after you have submitted your application, and furthermore, that they might not be automatically requested for all candidates. You may wish to alert your letter writers in advance, so they will be ready to submit your letter.
Preferred
Experience with machine learning, natural language processing or a related field.
Experience with deep learning platforms, such as PyTorch or Tensor Flow.
Experience with large datasets and distributed computing.
Experience in working with biomedical data.
Passionate about real-world applications and impact.
Proficient verbal and writing communication skills.
Track record of publications in top ML or NLP venues.