About the job
As an AI Scientist Intern on our Computational Protein Design team, you will work alongside talented scientists and engineers developing generative AI models for protein and antibody therapeutic design. During your internship, you will contribute to advancing state-of-the-art machine learning models for biology, with a focus on impacting protein/antibody design and drug discovery. You will also have the opportunity to collaborate with interdisciplinary experts in biology, drug discovery, and clinical research.
Responsibilities
Develop and apply deep learning methods for protein/antibody structure, sequence, or property modeling, under the guidance and mentorship of experienced scientists and engineers
Implement and train models on GPUs using PyTorch
Contribute to ongoing research projects involving protein structure, sequence, or biophysical/affinity datasets
Participate in discussions to help generate innovative ideas for advancing AI methodologies in computational protein design
Document findings and communicate progress effectively to peers and mentors
Qualifications
Minimum
Currently pursuing a MS or PhD in Computer Science, Machine Learning, or a related technical field, with strong publication record
Hands-on experience with PyTorch and training/inference of AI models on GPUs
Strong interest in AI innovation and its applications to interdisciplinary fields such as biology and chemistry
Extensive hands-on experience with deep learning methods and frameworks
Ability to work collaboratively in a team environment and learn from experienced mentors
A scientifically curious mindset with a passion for exploring new challenges
Prior research experience demonstrated through publications and/or significant open source code authorship
Preferred
Experience with large-scale distributed training and inference is a plus
Exposure to molecular structure or biological sequence data or computational biology/bioinformatics is a plus, but not required
Interest in contributing to open-source deep learning libraries and frameworks is a plus