Modern biomedical research is becoming increasingly quantitative and reliant on computational methods, with growing use of large and complex datasets to address biomedical research questions and advance human health. To help address the need for biomedical researchers with cutting-edge computational and quantitative skills, we have updated the focus areas of our Predoctoral T32 Training Program in Computational Biology, Bioinformatics, and Biomedical Data Science (formerly called Bioinformatics and Computational Biology). In doing this, we aim to better integrate training in data-science approaches throughout the curriculum and during the mentored research period. We are now placing a strong emphasis on programs that:
- Focus on new and emerging areas of data science, including machine learning, deep learning, and artificial intelligence.
- Integrate training in biological sciences and quantitative and computational sciences (e.g., data science, computer science, statistics, mathematics, informatics, engineering).
- Provide multidisciplinary training to students in the fundamentals and applications of computational and information sciences.
- Include training in fair and ethical data use, data sharing, and data security and confidentiality.
- Take advantage of the resources and expertise available in the private sector to develop student skills such as the ability to write efficient, industry-standard computer code and the use of emerging technologies and platforms.
- Help develop career pathways for trainees, including by forming internship/training partnerships with industry and other sectors.
These changes will be effective with the January 25, 2019, application receipt date.
For more information about the changes to the focus areas for this training program, please see the NIH Guide Notice, and the NIGMS Predoctoral T32 Training Program website. As usual, we welcome your comments and suggestions.