Director, Data Science Platform | Data Science Platform

Reporting to the Chief Information Officer, and working primarily with Faculty, Research Staff, Postdoctoral Fellows, and Graduate Students, the Director leads a team of seven (7) Machine Learning Engineers that identify and work closely with internal and external resources to determine how to most effectively support University researchers’ needs for applying ML/AI and/or other quantitative approaches to new and existing data sets across a wide variety of disciplines, including structural biology, imaging, microscopy, “omics,” neuroscience, immunology/virology, and the physical sciences. The position also includes leadership of the Fisher Center AI Platform, which seeks to apply AI/ML techniques to understand the causes of Alzheimer's disease, improve the care of people living with it, and find a cure. 

Responsibilities include, but are not limited to the following:

• Consult on experimental design and best usage, with emphasis on best practices for proper analysis and reproducibility;
• Recruit and manage Data Science Platform staff members;
• Develop and lead training/classes in ML/AI fundamentals and techniques; adapt and evolve training to best serve the changing needs of the research community;
• Identify, improve, and/or create appropriate training data sets for ML/AI projects;
• Advise researchers and collaborators on method selection and implementation, as well as on how to direct research projects to ensure alignment with emerging advancements in deep learning;
• Maintain awareness of advances in the field and their applicability to problems of interest to members of Rockefeller’s research community;
• Identify and apply for appropriate grant funding opportunities;
• Additional duties and special projects as assigned.

REQUIRED QUALIFICATIONS:

• Ph.D. or equivalent degree in data science, machine learning, artificial intelligence, computer science, electrical engineering, statistics or a related field.
• A minimum of ten (10) years of research experience in identifying, formulating and solving biological problems through the application of advanced artificial intelligence technologies.
• At least two (2) years of leadership experience.
• A strong publication record in top-tier venues focused on machine learning, artificial intelligence or their domain-specific applications, such as AAAI, NeurIPS, ICML, ICLR, IJCAI, KDD, ICCV, ECCV, CVPR, EMNLP, ACL, MICCAI, IJCV, TPAMI, TIP, ACM-MM, Nature, Nature Methods, Science and equivalent conferences and journals.
• Broad knowledge on recent advances in artificial intelligence, such as foundation models (including large-language models, vision-language models, genomic foundation models, etc.), generative models, self-supervised learning, large-scale distributed training, efficient deep learning, with research expertise in at least one relevant field.
• Basic knowledge of the deep learning tool stack, such as PyTorch, Python, CUDA, Linux, and computing cluster management.
• Must possess excellent communication and interpersonal skills.

PREFERRED QUALIFICATIONS:

• Prior work experience in a research related, academic environment is a plus.  

The Rockefeller University is an equal opportunity employer – veterans/individuals with disabilities. Qualified applicants will receive consideration for employment without regard to characteristics protected by applicable local, state or federal law, including but not limited to disability and protected veteran status.

The salary of the finalist selected for this role will be set based on various factors, including but not limited to organizational budgets, qualifications, experience, education, licenses, specialty, and training. The hiring range provided represents The Rockefeller University's good faith and reasonable estimate of the range of possible compensation at the time of posting.