Offer summary

Qualifications:

Knowledge of organic chemistry at the undergraduate level or higher is required., Proficiency in Python programming is required., Experience with a cheminformatics toolkit (e.g., RDKit, Openeye) is required., Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch) is desirable..

Key responsabilities:

Explore generative AI approaches for drug design and synthetic pathway generation.

Create training, validation, and test sets for generative AI models.

Run generative methods on protein targets and evaluate the results for synthetic accessibility.

Prepare and present results at internal meetings and summarize work at the conclusion of the internship.

Job description

Arvinas is a clinical-stage biotechnology company dedicated to improving the lives of patients suffering from debilitating and life-threatening diseases through the discovery, development, and commercialization of therapies that degrade disease-causing proteins. Arvinas uses its proprietary PROTAC Discovery Engine platform to engineer proteolysis targeting chimeras, or PROTAC targeted protein degraders, that are designed to harness the body’s own natural protein disposal system to selectively and efficiently degrade and remove disease-causing proteins. In addition to its robust preclinical pipeline of PROTAC protein degraders against validated and “undruggable” targets, the company has three investigational clinical-stage programs: ARV-766 and bavdegalutamide for the treatment of men with metastatic castration-resistant prostate cancer; and vepdegestrant (ARV-471) for the treatment of patients with locally advanced or metastatic ER+/HER2- breast cancer. Arvinas, as part of its overall business strategy, selectively assesses opportunities for potential collaboration, license, marketing and royalty arrangements, and similar transactions, to advance and accelerate the development and enhance the commercial potential of its product candidates.

#TeamArvinas is made up of approximately 450 passionate and curious employees, whose diverse thoughts and perspectives are highly valued. Arvinas employees embrace the freedom to pursue innovation, think creatively, and give back. They are driven by the company’s values and mission – to improve the lives of patients with serious diseases by pioneering therapies created with our revolutionary PROTAC® protein degradation platform. We’re really excited about the work we’re doing inside and outside of Arvinas, and think you will be, too. But don’t just take our word for it – learn more about life at Arvinas and what employees have to say.

For more information, please visit www.arvinas.com.

Position Summary

The internship project will explore de novo molecular design using generative AI models and have a focus on evaluating existing public domain implementations of algorithms for synthetic pathway generation. Collaborating closely with members of the Arvinas CADD team, the intern will configure, run, and deploy generative models. Additionally, the intern will compare the results of the generative methods to evaluate how well they produce synthetically tractable molecules for protein targets of interest. The intern will present results at CADD team meetings and at the conclusion of the internship will summarize their work as a talk or poster at Arvinas.

This position reports to a Research Investigator, Computational Chemistry and can be located remotely within the U.S.

Principal Responsibilities

Key responsibilities of this role include, but are not limited to:

Explore generative AI approaches for de novo drug design and synthetic pathway generation.
Dive deep into molecular datasets, creating statistically rigorous training, validation, and test sets to optimally retrain generative AI models for real-world prediction and generation tasks.
Run generative methods on protein targets of interests and evaluate the quality of the results with an emphasis on synthetic accessibility of the designed molecules.
Prepare and present results at an internal Arvinas function at the conclusion of the internship.

Qualifications

A knowledge of organic chemistry at the undergraduate level or higher is required.
Proficiency in Python programming required.
Experience with a cheminformatics toolkit (RDKit, Openeye, Schrodinger, etc.) is required.
Experience using version control (GitHub, GitLab, Bitbucket, etc.) required.
Experience working on medicinal chemistry projects is desirable.
Knowledge of and experience with at least one ML framework (TensorFlow, PyTorch or Keras) is desirable.
Knowledge of RNNs, LSTMs, Transformers and LLMs is desirable.
Must be able to work effectively in both independent and team contexts.
Arvinas will not be providing VISA sponsorship for this position. You must have the ability to work without a need for a current or future VISA sponsorship.

Remote (Home office based):

The duties of this role are generally conducted in a home office environment. Employees must be able, with or without an accommodation to use a computer; engage in communications via phone, video, and electronic messaging; engage in problem solving and non-linear thought, analysis, and dialogue; collaborate with others; maintain general availability during standard business hours.

Education

Computational Chemistry/Biology, Chemistry, Biology, or Computer Science major.
Completion of classes in Computational Chemistry, Chemistry, and/or Molecular Biology & Biophysics strongly preferred.
Preference for doctoral graduate students nearing degree completion.

#LI-Remote

Arvinas is proud to offer a competitive package of base and incentive compensation as well as a comprehensive benefits program designed to support the health, wellness and financial security of our employees and their families. Benefits include group medical, vision and dental coverage, group and supplemental life insurance, and much more. To learn more about Arvinas, please visit www.arvinas.com

Arvinas is an Equal Opportunity employer

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