| Microsoft Careers

Microsoft

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On-site
Location
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Posted
56 days ago

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Similar $180k
$106k most similar roles pay here $248k

This listing doesn't post a salary. Most similar roles pay $152,150–$207,350.

Based on 239 similar postings.

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About Microsoft

Microsoft Corporation is a global technology leader producing software, hardware, and cloud services including Windows, Office 365, Azure cloud platform, Xbox gaming, and Surface devices. Industry: Software & Cloud Computing

Microsoft currently has 1580 open roles on FindRole.

Listed pay typically runs $119,800–$234,700 across 1408 roles with salary data.

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At a glance

TL;DR · | Microsoft Careers

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This Research Internship at the intersection of geometric computer vision, Bayesian statistical theory, and approximation algorithms seeks a PhD candidate to develop Bayesian methods for 2D and 3D point matching. The role involves implementing efficient approximation algorithms in Python or C++ and benchmarking them against traditional techniques, with an emphasis on producing a high-quality technical report for publication. Ideal candidates have research-level expertise in geometric computer vision, Bayesian theory, and approximation algorithms, along with strong coding skills and the ability to write clear technical reports. The project aims to address fundamental challenges in robot navigation, 3D scene reconstruction, and AR/VR asset generation by advancing statistical methods beyond maximum likelihood estimation towards more robust Bayesian approaches.

Skills

Python C++ Bayesian theory RANSAC maximum likelihood estimation Jeffreys' priors marginalization techniques computational complexity classes geometric computer vision

What you'll do

  • Develop Bayesian methods for 2D and 3D point matching in geometric computer vision.
  • Implement approximation algorithms efficiently using Python or C++.
  • Benchmark developed methods against existing techniques in the field.
  • Write high-quality technical reports detailing research findings and methodologies.
  • Apply knowledge of geometric computer vision, including pinhole camera models and homographies.
  • Utilize Bayesian statistical theory to enhance accuracy in point matching problems.

What we're looking for

  • Currently enrolled in a PhD program in Mathematics, Statistics, Computer Science or related STEM field.
  • Completed graduate coursework in geometric computer vision and Bayesian statistical theory.
  • Proficiency in implementing efficient algorithms in Python or C++.
  • Experience with writing technical reports and scientific publications.
  • Understanding of approximation methods for discrete problems and computational complexity classes.

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