Interested in Deep Learning in Medicine @ Harvard? Apply today

We are looking for excellent candidates that want to apply deep learning algorithms to medical problems. This will be done at the cross-section of clinical fields (including radiology, oncology, and cardiology) with deep learning and computer science. For this we have access to unique datasets from research institutions throughout the United States and Europe.

We have several openings:

Postdoctoral Fellows in medical data analysis (including imaging and NLP): We are looking for candidates with a completed (or almost completed) PhD degree (or equivalent) in Computer Science, Data Science, Artificial Intelligence, (Biomedical) Engineering, Machine Learning, or related subject. Significant experience developing and testing deep learning networks is required, and experience in medicine is a plus. Familiarity with the state-of-the-art in the literature and beyond, as well as the eagerness to test and improve existing AI implementations. Demonstrated publication record in top-tier journals/conferences is required. Mastery of python and expertise with at least one deep learning framework (Tensorflow, PyTorch ..etc). Interest in medical applications and collaborating with medical professionals are essential. This position is located in Boston and the postdoctoral fellow will be appointed at Harvard Medical School. 

Graduate / PhD Students: We are looking for candidates with a completed (or almost completed) MSc degree (or equivalent) in Computer Science, Data Science, Artificial Intelligence, (Biomedical) Engineering, Machine Learning, or related subject. No prior experience in medicine is required; however, significant knowledge about deep learning and programming is a must. Interest in medical applications and collaborating with medical professionals are essential. This position is located in Boston and the applicant will be embedded in a joint program between AIM and Maastricht University, and is expected to graduate with a PhD degree from Maastricht University within four years.

Deep Learning Engineers: We are looking for a candidate with a MSc or PhD (or equivalent) in Computer Science, (Biomedical) Engineering, Artificial Intelligence, Machine Learning, or related subject. Theoretical Knowledge of machine learning principles, and deep learning in particular is required. Proven experience developing and testing deep learning networks, with focus on computer vision applications. Familiarity with the state-of-the-art in the literature and beyond is desired, as well as the eagerness to test and improve existing AI implementations. Mastery of python and expertise with at least one deep learning framework (Tensorflow, PyTorch ..etc). Ability to implement custom neural networks by extending the functionality of these frameworks. At least five years of experience in academic or industrial settings. This position is located in Boston with an appointment at Harvard Medical School.

To apply, please send an email (with position mentioned in the subject) including a cover letter and Curriculum Vitae (including three references) to Dr. Hugo Aerts.

Student Interns: We are looking for outstanding students (undergraduates and/or high schoolers) with strong interest and aptitude in Computer Science, Data Science, Artificial Intelligence, Machine Learning, or related subject. Interest in medical applications and collaborating with medical professionals are essential. No prior experience in medicine is required; however, proficiency in Python and familiarity with machine and deep learning frameworks is preferred. This mentored role is located in Boston at AIM headquarters. The candidate will have the opportunity to gain exposure to the field of applied artificial intelligence and oncology while learning from and working alongside expert oncologists, data scientists, and machine learning engineers. Please note: at this time, we are unable to sponsor international visas for student intern positions.

Note: At this time, our intern positions for 2023 are full. Please check back in fall 2023 for information on applying for our 2024 positions.