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To start the application process, you will need an updated CV or resume and a current unofficial or official transcript in English. Click on the “Apply” button on this page and provide the required materials in the appropriate sections (PDFs preferred):

1. In the “Resume Section:” attach an updated CV or resume. Please make sure also to include the following in it, all consolidated in a single PDF:

1. Research work: Projects, Publications, Research experience and References (if any)

2. Statement of purpose (no more than 500 words), detailing reasons for your interest in the Pre-doctoral Researcher role.

2. Please ensure you’ve listed your graduation date (in MM/YY)

3. In the “Education Section:” attach a current or recent unofficial or official transcript in English. Under “Degree Status,” select “Now attending/Graduated” to upload a transcript.

The Pre-Doctoral Researcher role is a 24-month role designed to give you experience working on challenging problems together with Google Deepmind India scientists and engineers in India before pursuing (or making a decision on pursuing) doctoral research.

As a Pre-Doctoral Researcher, you will collaborate with researchers, scientists, and engineers at Google Deepmind India working on fundamental research and applied problems in a wide range of areas in Computing. You will have a wide range of opportunities from conducting fundamental research and exploring their applications in products and services used by people, and conducting research that contributes to human-centered AI and catalyzes AI for Social Good. We expect our Pre-Doctoral Researchers to publish their high quality work externally.

Google Deepmind India addresses challenges that define the technology of today and tomorrow. From conducting fundamental research to influencing product development, our research teams have the opportunity to impact technology used by billions of people every day.

Our teams aspire to make discoveries that impact everyone, and core to our approach is sharing our research and tools to fuel progress in the field -- we publish regularly in academic journals, release projects as open source, and apply research to Google products.

• Work with research mentors to formulate research projects and/or novel applications of machine learning.
• Conduct research and publish high quality work.
• Implement algorithms, experiments, and/or human-computer interfaces using frameworks such as TensorFlow.
• Learn and understand research in machine learning algorithms.
• Understand how to use research to drive design decisions.