Microsoft Applied Science PhD Internship Opportunities – Redmond 

Taiwan, Taoyuan City 

965501388

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.

Required Qualifications:

• Currently pursuing a Doctorate Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field.
• Must have at least one additional quarter/semester of school remaining following the completion of the internship.
• 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.

Other Requirements:

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

The base pay range for this internship is USD $6710.00 - $13270.00 per month. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $8760.00 - $14360.00 per month.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:

• 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