INTERNSHIP DETAILS

Applied Science: PhD Internship Opportunities - Brazil

CompanyMicrosoft
LocationBrazil
Work ModeOn Site
PostedJanuary 28, 2026
Internship Information
Core Responsibilities
Interns will analyze and improve the performance of advanced algorithms on large-scale datasets and contribute to the development of intelligent solutions through data analysis and machine learning. They will also assist in preparing datasets for modeling and help adapt cleaned data for machine learning purposes.
Internship Type
full time
Company Size
227077
Visa Sponsorship
No
Language
English
Working Hours
40 hours
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About The Company
Every company has a mission. What's ours? To empower every person and every organization to achieve more. We believe technology can and should be a force for good and that meaningful innovation contributes to a brighter world in the future and today. Our culture doesn’t just encourage curiosity; it embraces it. Each day we make progress together by showing up as our authentic selves. We show up with a learn-it-all mentality. We show up cheering on others, knowing their success doesn't diminish our own. We show up every day open to learning our own biases, changing our behavior, and inviting in differences. Because impact matters. Microsoft operates in 190 countries and is made up of approximately 228,000 passionate employees worldwide.
About the Role
Overview

Come build community, explore your passions and do your best work at Microsoft with thousands of university interns from every corner of the world. This opportunity will allow you to bring your aspirations, talent, potential – and excitement for the journey ahead.  

 

As an Applied Science PhD Intern at Microsoft, you will be at the forefront of technological innovation, working collaboratively to bring research to life in our products and services. You'll gain expertise in cutting-edge research areas, apply advanced concepts to real-world needs, and use state-of-the-art tools to make a tangible impact on product quality and business outcomes. You'll contribute to the creation of intelligent solutions through data analysis, modeling, machine learning, and/or AI, LLM, SLM and agent, ensuring our products remain at the leading edge of innovation. 

 

As an intern at Microsoft, you’re stepping into a world of real impact from day one. You’ll collaborate with global teams on meaningful projects, explore cutting-edge technologies like AI, and kick start your career while doing it. With a strong focus on learning and development, this is your opportunity to grow your skills, build community, and shape your future—all while being supported every step of the way.  

 

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate and empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.   

 

Internship length will be from 4 to 6 months. Earliest start dates in June 2026. 

 

Please note this application is only for internships based in Brazil. For internships in other countries, please see our Careers site.



Responsibilities
  • Analyze and improve performance of advanced algorithms on large-scale datasets and cutting-edge research in machine intelligence and machine learning applications.
  • Think through the product scenarios and goals, identify key challenges, then fit the scenario asks into Machine Learning (ML) tasks, design experimental process for iteration and optimization.
  • Implement prototypes of scalable systems in AI applications.
  • Gain an understanding of a broad area of research and applicable research techniques, as well as a basic knowledge of industry trends and share your knowledge with immediate team members.
  • Prepare data to be used for analysis by reviewing criteria that reflect quality and technical constraints. Reviews data and suggests data to be included and excluded and be able to describe actions taken to address data quality problems.
  • Assist with the development of usable datasets for modeling purposes and support the scaling of feature ideation and data preparation.
  • Help take cleaned data and adapt for machine learning purposes, under the direction of a senior team member.


Qualifications

Required Qualifications:

  • Currently pursuing a Doctorate Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field.
  • Candidate must be enrolled in a full time bachelor's, masters, MBA, or PhD program in area relevant for the role during the academic term immediately before their internship. 
  • Business fluency in English (read, write, speak). 

 

Other Requirements:

  • Ability to submit an official or unofficial academic transcript as part of the evaluation process, if selected for interviews.

 

#EiP #PhD #PhDInternship #AppliedSciences #M365


This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.




Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Key Skills
Data AnalysisMachine LearningAIModelingResearch TechniquesData PreparationAlgorithm PerformancePrototypingStatistical AnalysisProgrammingCollaborationProblem SolvingCommunicationTechnical ConstraintsFeature IdeationExperimental Design
Categories
TechnologyScience & ResearchData & AnalyticsEngineeringEducation