Vilya is a computational biotechnology company creating a novel class of medicines to precisely target disease biology. We believe computational approaches are an integral, if not foundational, component of drug discovery and development.
We are harnessing the power of our platform to go after previously impossible targets in an array of indications. Vilya's ultimate goal is to solve some of the most challenging unmet medical needs that exist today.
Our Vision: Harness a revolution in technology and biology to better human health.
Our Mission: Build an independent, leading biotech company founded on intelligent drug design to cure the incurable.
We are seeking a highly-motivated, creative, and knowledgeable Deep Learning Intern to help develop internal methods at Vilya on the ML/DL Design team. As an intern, you will be responsible for developing and maintaining state of the art machine learning models and tools that help power Vilya's platform to design new therapeutics.
Responsibilities
- Design, develop, and maintain a real-world deep learning framework that improves or expands upon Vilya's macrocycle drug design pipeline.
- Collaborate and communicate with fellow experts in deep learning as well as the broader interdisciplinary Vilya team, including our research scientists in chemistry and biology.
- Get hands-on experience working with heterogeneous data gathered by our chemistry and biology teams, including a variety of in vitro assay measurements.
Basic Qualifications
- Current PhD student in computer science, computational biology, bioinformatics, or a field applicable to computational drug discovery.
- Strong background in the fundamentals of machine learning, including linear algebra, calculus and statistics.
- Experience developing, deploying, and managing deep learning models and formatting large datasets for real-world problems.
- Proficiency in Python and PyTorch.
- Ability to work well with an interdisciplinary team and to communicate complex scientific ideas to diverse audiences.
- Ability to work on site in our Seattle, WA office. No relocation costs will be provided through this internship.
Preferred Qualifications
- Experience with Slurm, Singularity, BigQuery and/or other cloud and high-performance computing infrastructure.
- Experience with concepts and deep learning techniques relevant to drug discovery and protein design, such as transformers, graph neural networks, equivariance, diffusion generative modeling, etc.
- Specific experience working with structure prediction or backbone diffusion models, such as AlphaFold, RosettaFold, Chroma, Proteus, etc.
- Experience working with reinforcement learning or active learning techniques, e.g. for optimizing molecules based on feedback from assays or expensive computational oracles.
- Experience with molecular property prediction, e.g. solubility, partition coefficients, toxicity, etc.
- Exposure to concepts in drug discovery such as ADME / Tox / DMPK.
Compensation
- Wage: $35.00/hr - $60.00/hr based on experience
- Commuter benefits
- Opportunity to work in a disruptive startup with a talented, experienced, and growing team of dedicated individuals
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