Computational Antibody Design Internship
1 week ago
Adimab is the leading technology provider for therapeutic antibody drug discovery, focusing solely on our partnerships without pursuing an internal product pipeline. Since 2009, we have partnered with over 100 pharmaceutical and biotechnology companies, generating more than 500 therapeutic programs, of which more than 70 have entered clinical trials.
Role Overview:
Adimab is seeking Computational Protein Design and Machine Learning/Data Science interns for summer 2024. You will have the opportunity to contribute to the development of computational methods for discovery and optimization of therapeutic antibodies and proteins, working closely with members of the Adimab Computational Biology and Antibody Engineering teams.
Multiple internship positions are available – projects will be tailored to individual interests and background, as well as company needs. Our goal is that our interns move projects forward in meaningful ways during their time at Adimab.
Location, timing, and compensation
- The internship will be fully on-site with our Computational Biology group located in Mountain View, California
- Start date in June 2024 for approximately 12-16 weeks
- Competitive compensation and relocation assistance (if applicable)
Responsibilities
- Application and/or development of Rosetta or Deep Learning-based approaches for protein structure prediction and design
- Train and improve ML (Machine Learning) models on Adimab’s proprietary experimental datasets to predict and improve antibody function and properties
Desired upon hire
- Currently pursuing a graduate degree in a relevant field (computational/structural biology, computer science, bioengineering, chemical engineering, chemistry, etc.).
- Ideal candidates will have completed their qualifying exam and 3-4 years of their PhD program with a publication/presentation record reflecting novel method development and application
- Prior experience creating, training, and deploying Deep Learning models
- Prior experience developing methods in the Rosetta macromolecular modeling suite, or similar software
- Preference for candidates with experience in developing or fine-tuning models for de novo design of protein structure and function (Diffusion, Hallucination, Inpainting, etc.), Large Language Models for proteins, or geometric deep-learning
- Experience developing machine learning methods and software in a collaborative team environment
- Strong programmer with proficiency in Python and Deep Learning frameworks (such as Tensorflow, PyTorch, etc.)
Come join us
Our integrated antibody discovery and engineering platform provides unprecedented speed from antigen to purified, full-length human IgGs with exquisite specificity and biophysical behavior. We offer fundamental advantages by delivering diverse panels of antibodies that meet the most demanding standards for affinity, epitope specificity, species cross-reactivity, and developability. We enable our partners to rapidly expand their biologics pipelines through a broad spectrum of technology access arrangements.
As a profitable privately-held biotech company, we take a long-term view on value creation and make substantial investments in technology development, research, and our people.
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