Scientific Co-Director, Data Science and Multimodal Integration

Massachusetts Institute of Technology; Cambridge (MA); On-site; USD 180,000 - 240,000; Full time

Job summary

A leading research institution is seeking a Scientific Co-Director for Data Science and Multimodal Integration to lead initiatives in AI and data science applications. This position involves directing the development and deployment of advanced methodologies, contributing to research outputs, and mentoring staff members. Ideal candidates will have a Ph.D. and extensive experience in AI/ML, with a proven track record in research and publication. The role requires strong leadership and expertise in multimodal data integration.

Qualifications

• Minimum of seven years postdoctoral or equivalent research experience.
• Evidence of original or collaborative scholarship documented by publications.
• Expertise in ML, DL, and statistical learning methods.

Responsibilities

• Direct development and deployment of advanced data science methods.
• Contribute to publications and grant applications.
• Lead development of training materials and mentorship activities.

Skills

AI/ML applications

Statistical learning

Data visualization

Multi-modal data integration

Programming skills

data visualization

EDA

multimodal data integration

leadership/supervisory

Education

Ph.D. in computer science or related field

Tools

ML/DL frameworks

Job description

Posting Description

SCIENTIFIC CO-DIRECTOR, DATA SCIENCE AND MULTIMODAL INTEGRATION (DSMI), Koch Institute (KI)

Koch Institute (KI) to direct the development and deployment of advanced data science and AI/ML methodologies in the KI community. This co-leader will maintain current understanding of data analyses and multimodal integration methods and develop novel methods leading to expanded DSMI services; review DSMI staff research output and direct deployment of new techniques; and significantly contribute to publications and grant applications. The leader will direct preparation of presentations for the community, lead development and presentation of training materials, and participate in mentorship activities.

Job Requirements

REQUIRED : Ph.D. in computer science, computational biology, data science, or a related field with a strong emphasis on AI/ML applications; a minimum of seven years postdoctoral or equivalent research experience applying AI, machine learning (ML), and deep learning (DL) techniques to biological data; experience must include evidence of original or collaborative scholarship documented by publications, software, or deployed intelligent systems; demonstrated expertise in statistical learning, ML, DL computer vision, and NLP methods applied to omics, imaging, and clinical datasets; programming skills with experience in ML/DL frameworks; data visualization and EDA expertise; multi-modal data integration and representation learning across diverse data types; and shared resource and leadership or supervisory experience.

PREFERRED : Experience with data governance, FAIR principles, and regulatory compliance; knowledge of explainable AI (XAI) techniques and their application in biomedical contexts; experience with federated learning or other advanced AI paradigms; experience integrating AI models into pipelines; and familiarity with biomedical ontologies, knowledge graphs, or semantic data integration.

3/3/2026