IISc, Applied Materials India ink R&D pact

Apart from IISc Bangalore, IIT Bombay, IIT Delhi, IIT Kanpur and IIT Kharagpur feature in the THE World University Rankings 2018, but at much lower positions. Photo: Hemant Mishra/Mint
Apart from IISc Bangalore, IIT Bombay, IIT Delhi, IIT Kanpur and IIT Kharagpur feature in the THE World University Rankings 2018, but at much lower positions. Photo: Hemant Mishra/Mint
 1 min read . Updated: 23 Mar 2021, 10:54 AM IST Staff Writer

BENGALURU: Applied Materials India, the local subsidiary of US materials engineering company Applied Materials Inc., has signed a research and development (R&D) pact with Indian Institute of Science (IISc), Bengaluru.

As part of the Industry Affiliate Program of the Centre for Nanoscience and Engineering (CeNSE), IISc Bengaluru and Applied Materials India will work closely with CeNSE to explore new applications and solutions in the field of advanced materials.

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Applied Materials India has forged an alliance with IISc to offer a ‘world-class infrastructure’ to take solutions from ‘lab to fab’ and provide a much-needed impetus to semiconductor technology and manufacturing in the country, it said in a statement.

The main goal of CeNSE is to carry out cutting-edge research and technological innovations and translate them with appropriate partners into successful commercial products and services.

“We intend to bring our expertise in nanoengineering to scale the level of commercial viability for key R&D initiatives. Our domain expertise in micro and nanoelectronics will create a platform that can accelerate advanced research and charter growth in whitespace areas," said Srinivas Satya, country president, Applied Materials India.

Applied Materials India engages with India’s premier engineering and technology institutes via industry-academia collaboration. Last year, it celebrated 15-years of collaboration with IIT Bombay in the field of nanoelectronics and energy. In 2018, Applied Materials India partnered with IIT Madras to boost research in artificial intelligence, machine learning and data science with applications in semiconductors and pharmaceuticals.

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