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Pre-Doctoral Researcher, University Graduate (Fixed-Term Contract)

Full Time On Site (Full Time) @Google in Research
  • Bengaluru, Karnataka, India View on Map
  • Post Date : October 17, 2021
  • Apply Before : November 16, 2021
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Job Description

Minimum qualifications:

  • Bachelor’s degree in a STEM field such as Computer Science, Mathematics, or Statistics, or equivalent practical experience.
  • Experience with Python, C/C++, or Java
  • Research experience in machine learning or AI techniques (e.g. open source project(s), campus lab experience, research internship(s), or publication(s)).

Preferred qualifications:

  • Ability to work and collaborate across multiple teams

About the job

The Pre-Doctoral Researcher role is a 24-month role designed to give you direct experience working on challenging problems together with research scientists and engineers in Bangalore before continuing your Computer Science research education.

As a Pre-Doctoral Researcher, you will collaborate with scientists and engineers at Google Research working on fundamental research and applied problems in a variety of areas in Computer Science. You will have a wide range of opportunities from conducting fundamental research, to contributing to products and services used by billions of people, and conducting research to catalyze AI for Social Good. We strongly encourage our Pre-Doctoral Researchers to publish their work externally.

Research happens at Google everyday, on many different embedded teams throughout the company. Our research reaches the user through both services and products such as Search, Maps, Google Assistant, Google Translate, Google Cloud and our computing, storage, and networking infrastructure. To achieve this, we’re working on a wide variety of projects that utilize the latest state-of-the-art technologies that push the boundaries of what is possible.

Responsibilities

  • Work with research mentors to formulate research projects and/or novel applications of machine learning.
  • Conduct research and publish it.
  • Implement algorithms, experiments and/or human-computer interfaces using frameworks such as TensorFlow.
  • Learn and understand a large body of research in machine learning algorithms.
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