Foundational AI Research Scientist

Join Intel AI Lab and contribute to groundbreaking research that will shape the future of computational chemistry and machine learning.  As a Foundational AI Research Scientist at Intel AI Lab, you will pioneer advanced machine learning techniques to revolutionize computational chemistry. Your work will integrate cutting-edge geometric deep learning and scalable machine learning methods to enhance traditional scientific computing processes. The results of your research will be disseminated through top-tier publications, open-source software, and direct technology transfers to Intel's business units for commercial application. 

In this role, your responsibilities will include:   

• Develop and implement novel machine learning models to accelerate computational chemistry. 

• Integrate state-of-the-art geometric deep learning and scalable machine learning techniques into scientific computing pipelines. 

• Publish research findings in top-tier conferences and journals. 

• Create open-source software tools for developers and practitioners. 

• Collaborate with Intel business units to transfer technology for commercial use. 

• Work effectively in a dynamic, team-oriented environment. 

• Communicate research outcomes and technical information clearly through written and verbal means. 

The successful candidate should exhibit the following behavioral traits:  

• Good analytical skills  

• Problem-solving skills  

• Independent work ethic  

• Intuitive thinking 

You must possess the below minimum education requirements and minimum required qualifications to be initially considered for this position. Relevant experience can be obtained through schoolwork, classes, project work, internships, and/or military experience. Additional preferred qualifications are in addition to the minimum requirements and are considered a plus factor in identifying top candidates. 

Minimum Qualifications:   

• PhD in Computer Science, Electrical Engineering, STEM-related field. (e.g., Statistics, Applied Math, Computational Neuroscience, etc.). 

• 1+ year of experience in: 

• Designing and training deep learning models and other machine learning techniques. 

• Contributing original research to the field of deep reinforcement learning, evidenced by peer-reviewed publications in top-tier conferences or journals. 

• Utilizing deep learning and machine learning frameworks such as PyTorch and TensorFlow.