Job Information
RTX Corporation Summer 2024, Intern: Computer Vision Research (Ph.D. students) in East Hartford, Connecticut
Date Posted:
2024-02-20
Country:
United States of America
Location:
RC1: United Tech Research Center 411 Silver Lane, East Hartford, CT, 06108 USA
Position Role Type:
Hybrid
RTX Corporation is an Aerospace and Defense company that provides advanced systems and services for commercial, military and government customers worldwide. It comprises three industry-leading businesses – Collins Aerospace Systems, Pratt & Whitney, and Raytheon. Its 185,000 employees enable the company to operate at the edge of known science as they imagine and deliver solutions that push the boundaries in quantum physics, electric propulsion, directed energy, hypersonics, avionics and cybersecurity. The company, formed in 2020 through the combination of Raytheon Company and the United Technologies Corporation aerospace businesses, is headquartered in Arlington, VA.
To realize our full potential, RTX is committed to creating a company where all employees are respected, valued and supported in the pursuit of their goals. We know companies that embrace diversity in all its forms not only deliver stronger business results, but also become a force for good, fueling stronger business performance and greater opportunity for employees, partners, investors and communities to succeed.
The following position is to join our RTX Research Center (RTRC):
Role Overview:
The Advanced Learning and Analytics team researches and develops machine learning, computer vision, reinforcement learning, large language models and human computer interaction solutions for a variety of high impact real world problems in the aerospace, manufacturing and defense industries.
We are looking for a 2024 summer intern to conduct research in the broad topic of 3D computer vision, computer graphics, structure from motion, 3D reconstruction, neural radiance fields, neural implicit surfaces and feature matching.
Primary Responsibilities:
Algorithm development, software implementation and model training for complex 3D computer vision applications
Communicating research results to internal and external stakeholders
Develop state of art machine learning and computer vision models and apply them to real world datasets at scale
Support for publishing results in top conferences
Work with a small focused team on developing 3D vision models
Learn about the broad areas of ML/CV applications in aerospace and defense
Required Qualifications:
Two years of PhD level research experience in broad area of computer vision and machine learning
Prior coursework in broad areas of computer vision and machine learning
Experience training complex ML pipelines for 3D vision applications
ML software and coding experience in Python and familiarity with ML frameworks like Pytorch, Tensorflow
Publication record in top venues like CVPR, NeurIPS, ICLR
Preferred Qualifications:
Three to Four years of PhD level research experience in any of the following topics: 3D computer vision, computer graphics, structure from motion, 3D reconstruction, neural radiance fields, neural implicit surfaces, feature matching
Demonstrated mathematical aptitude in the areas of computer vision, machine learning
Ability to set research direction and work independently.
Education:
Candidates must be currently pursuing a PhD degree in computer science, electrical engineering, or related field with a focus on computer vision. A minimum 3.8 GPA is required. Please submit a copy of your academic transcripts with your application.
Location:
Remote or Hybrid.
Work Authorization:
Must be authorized to work in the U.S. without sponsorship now or in the future. RTX will not offer sponsorship for this position.
The salary range for this role is 37,000 USD - 82,000 USD. The salary range provided is a good faith estimate representative of all experience levels. RTX considers several factors when extending an offer, including but not limited to, the role, function and associated responsibilities, a candidate’s work experience, location, education/training, and key skills.
Hired applicants may be eligible for benefits, including but not limited to, medical, dental, vision, life insurance, short-term disability, long-term disability, 401(k) match, flexible spending accounts, flexible work schedules, employee assistance program, Employee Scholar Program, parental leave, paid time off, and holidays. Specific benefits are dependent upon the specific business unit as well as whether or not the position is covered by a collective-bargaining agreement.
Hired applicants may be eligible for annual short-term and/or long-term incentive compensation programs depending on the level of the position and whether or not it is covered by a collective-bargaining agreement. Payments under these annual programs are not guaranteed and are dependent upon a variety of factors including, but not limited to, individual performance, business unit performance, and/or the company’s performance.
This role is a U.S.-based role. If the successful candidate resides in a U.S. territory, the appropriate pay structure and benefits will apply.
RTX anticipates the application window closing approximately 40 days from the date the notice was posted. However, factors such as candidate flow and business necessity may require RTX to shorten or extend the application window.
RTX is An Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status, age or any other federally protected class.
Privacy Policy and Terms:
Click on this link (http://www.rtx.com/privacy/Job-Applicant-Privacy-Notice) to read the Policy and Terms
Raytheon Technologies is An Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status, age or any other federally protected class.