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InstaDeep Info Session

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Event Date: Wednesday, February 7, 2024
Event Time: 3:15 PM to 4:30 PM
Event Address: Room 100 Mudd Hall (Seeley G. Mudd Bldg, 1798 Scenic Ave, Berkeley, CA 94709)

 

Founded in 2014, InstaDeep is a pioneering AI company at the forefront of innovation. With strategic offices in major cities worldwide, including London, San Francisco, Boston, Paris, and Berlin, InstaDeep collaborates with giants like Google DeepMind and prestigious educational institutions like Stanford, MIT, Berkeley, Oxford, and UCL. InstaDeep, a Google Cloud Partner and a select NVIDIA Elite Service Delivery Partner, has been listed among notable players in AI, fast-growing companies, and Europe's 1000 fastest-growing companies in 2022 by Statista and the Financial Times. InstaDeep's acquisition by BioNTech in 2023 has further solidified their commitment to leading the industry.

Learn more here: https://www.instadeep.com/

Join us on Wednesday, February 7 to learn more about the innovative work happening at InstaDeep and the career opportunities available at the company.

Narimane Hennouni

Narimane Hennouni: I’m an ML Research Engineer at InstaDeep in the San Francisco office and WomenTech Makers Ambassador.

Rick Gentry

Rick Gentry: I’m a Research Engineer at InstaDeep and have had the privilege of contributing to groundbreaking projects at our company. I am excited to share the compelling and impactful strides we are making at InstaDeep, utilizing AI to tackle real-world challenges.

INSTADEEP London UK Tuesday, April 18, 2023 (Elizabeth Dalziel)

Alain-Sam Cohen: I joined InstaDeep around 6 years ago and built our Engineering (think Applied ML) teams in the UK and the US. I also started our San Francisco office last year, where we apply machine learning algorithms to real-world problems, such as combinatorial optimization, insurance claims, and computational biology.

The team has worked on a diverse set of projects from employing graph neural networks and large language models to predict properties of proteins from their RNA sequences to automating claims processing by fusing tabular machine learning and language models.