Intern 2026: Computational approaches to design de-novo molecules

IBM Research takes responsibility for technology and its role in society. Working in IBM Research means you'll join a team who invent what's next in computing always choosing the big urgent and mind-bending work that endures and shapes generations. Our passion for discovery and excitement for defining the future of tech is what builds our strong culture around solving problems for clients and seeing the real world impact that you can make.

IBM's product and technology landscape includes Research Software and Infrastructure. Entering this domain positions you at the heart of IBM where growth and innovation thrive.

The aim of this project is to design de novo proteins that can sense and manipulate the plasma membrane which is critical for cells to execute important physiological functions e.g. cell motility endocytosis. In collaboration with the experimentalists we designed different protein structures and performed preliminary validation using full atom molecular dynamic simulations. In this way we could assess whether the predicted protein–membrane interactions were capable of driving membrane curvature. After confirming the design’s behavior through in-silico simulations we subsequently validated it using in-vitro experiments.

As a research scientist intern you will work closely with an assigned mentor and will analyze the already collected data by building your own codes or using standard tools for analyzing trajectories from atomistic simulations. You will contribute to designing the analysis and making improvements to the current status of the project. You will also be expected to contribute to write a research report or paper on your internship project and present your work at internal research meetings and external workshops and/or conferences.

• Background in Computational Biochemistry Computer Science Machine Learning Bioinformatics or a related field.
• Proficiency in Pythonand technologies like TensorFlow PyTorch.
• Familiarity with high-performance computing environmentsand DevOps tools (GitHub Actions).

• Proficiency in test-driven development practices to ensure robust and scalable workflows.
• Proven success in collaborating across disciplines to deliver innovative solutions.
• Deep knowledge of computational biology biochemistry and/or materials science