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    • Designing and running the synthesis for main materials.
    • Mainly organic synthesis, but simple inorganic will be present.
    • Conduct open source research in relevant regional languages in response to defined tasking.
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    • Strong analytical and research skills.
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    • Designing and running the synthesis for main materials.
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    • Full-time - 37.5 hours per week, Permanent.
    • Salary - £50,000 - £55,000 per annum (depending on experience).
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    • You will travel to respondent’s homes to conduct face-to-face interviews and ensure respondents feel comfortable sharing their opinions.

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Job Post Details

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2026 Applied Scientist Intern, Amazon University Talent Acquisition - job post

AWS EMEA SARL (UK Branch) - F93
(part of Amazon.com)
3.4 out of 5 stars
London
Full-time

Location

London

Full job description

DESCRIPTION

Are you a MS or PhD student interested in a 2026 internship in the field of machine learning, deep learning, generative AI, large language models and speech technology, robotics, computer vision, optimization, operations research, quantum computing, automated reasoning, or formal methods? If so, we want to hear from you!

We are looking for students interested in using a variety of domain expertise to invent, design and implement state-of-the-art solutions for never-before-solved problems.

You can find more information about the Amazon Science community as well as our interview process via the links below;

https://www.amazon.science/

https://amazon.jobs/content/en/career-programs/university/science

https://amazon.jobs/content/en/how-we-hire/university-roles/applied-science

Key job responsibilities
As an Applied Science Intern, you will own the design and development of end-to-end systems. You’ll have the opportunity to write technical white papers, create roadmaps and drive production level projects that will support Amazon Science.

You will work closely with Amazon scientists and other science interns to develop solutions and deploy them into production. You will have the opportunity to design new algorithms, models, or other technical solutions whilst experiencing Amazon’s customer focused culture.

The ideal intern must have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems.

A day in the life
At Amazon, you will grow into the high impact person you know you’re ready to be. Every day will be filled with developing new skills and achieving personal growth.

How often can you say that your work changes the world? At Amazon, you’ll say it often. Join us and define tomorrow.

Some more benefits of an Amazon Science internship include;

  • All of our internships offer a competitive stipend/salary
  • Interns are paired with an experienced manager and mentor(s)
  • Interns receive invitations to different events such as intern program initiatives or site events
  • Interns can build their professional and personal network with other Amazon Scientists
  • Interns can potentially publish work at top tier conferences each year

About the team
Applicants will be reviewed on a rolling basis and are assigned to teams aligned with their research interests and experience prior to interviews.

Start dates are available throughout the year and durations can vary in length from 3-6 months for full time internships.

This role may available across multiple locations in the EMEA region (Austria, Estonia, France, Germany, Ireland, Israel, Italy, Jordan, Luxembourg, Netherlands, Poland, Romania, Spain, South Africa, UAE, and UK).

Please note these are not remote internships.

BASIC QUALIFICATIONS

  • Experience programming in Java, C++, Python or related language
  • Enrolled in a PhD or Master's degree in Computer Science, Machine Learning, Engineering, Operations Research, Statistics or related fields

PREFERRED QUALIFICATIONS

  • Have publications at top-tier peer-reviewed conferences or journals
  • Experience in designing experiments and statistical analysis of results
  • Experience implementing algorithms using toolkits and self-developed code
  • Experience in solving business problems through machine learning, data mining and statistical algorithms

Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
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