Research Intern - Biomedical AI for Precision Health

Research Interns put inquiry and theory into practice. Alongside fellow doctoral candidates and some of the world's best researchers, Research Interns learn, collaborate, and network for life. Research Interns not only advance their own careers, but they also contribute to exciting research and development strides. During the 12-week internship, Research Interns are paired with mentors and expected to collaborate with other Research Interns and researchers, present findings, and contribute to the vibrant life of the community. Research internships are available in all areas of research, and are offered year-round, though they typically begin in the summer. The Research Intern will collaborate with a team of top-notch scientists, engineers, and biomedical practitioners to: 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. Currently enrolled in a PhD program in Computer Science, or a related STEM field. 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. 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.

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