Crowd Science Intern (Available June 2024)

Job Title

Crowd Science Intern

Job Location

This role will be available to candidates in New York, Boston, or Chicago offices.

Job Overview

Arup’s Transportation, Logistics, and Urban Planning (TLUP) works with public and private sector clients who are eager to embrace innovation, sustainability, and social impact in planning. Our work includes network optimization to improve opportunity accessibility, traffic modeling and simulation to help engineers identify ways to relieve congestion without costly new construction, and multi-modal planning for campuses that want to be meaningfully integrated with the surrounding neighborhood.

We are looking for a candidate to join our multi-disciplinary Crowd Science team which consists of Pedestrian Planners who solve complex pedestrian flow based questions, typically using agent based simulation tools. You will bring a human-centered perspective to support operational, planning and design teams that are delivering large scale, complex, pedestrian specific projects in order to provide an exemplary experience for the humans that use these places. You will have a high level understanding of traditional planning processes and methodologies but most importantly have core skills in all or either of machine learning, computer vision, 3D visualization/game development, or software development. You’ll have a creative approach to solving complex problems and be interested in new and innovative applications of your traditional skills. The role will entail completing a project that aligns with the core work done by our Crowd Science team to support their work in data collection, visualization and/or developing new software tools. Your contributions will likely be utilized across Arup’s global community of Pedestrian planners.

Compensation

New York City Hiring Range - The good faith base salary hiring range for this job if performed in New York City, NY is $26.00 to $37.00 per hour. Please note hiring ranges for candidates performing work outside of New York City, NY will differ.

Responsibilities

Responsibilities of this specific role will include, but not be limited to the following:

• Development of new code and automation building in ideally Python but also C++, SQL or Java.
• Perform Arup internal user research interviews.
• Data collection and manipulation.
• Development of new software.
• Develop and improve agent-based simulation models of pedestrian flow.
• Conduct research on crowd behavior.
• Analyze data from pedestrian surveys and experiments.
• Collaborate with engineers and architects to design and implement crowd management solutions.
• Undertake a project set for you around your area of interest: machine learning, software development, or visualization.

Requirements

Required:

Candidate should have the qualifications below in one of the three named streams.

• Must be pursuing a Bachelor’s or Master’s degree.
• Candidate must be eligible to work in the US without the need for employer sponsored work authorization now or in the future.

Stream 1: Machine Learning

• Computer vision background.
• Familiarity with processes for training computer vision models.
• Familiarity with OpenCV and TensorFlow.

Stream 2: 3D Visualization

• Familiarity with 3D modeling and/or animation including the use of Unreal Engine, Maya, 3DSMax, or SketchUp or another software platform.
• Game development or software development background.

Stream 3: Software developer

• Demonstrated interest in software development.
• Ability to develop small programs centered on data storage and management.
• Ability to develop basic graphical user interfaces (GUI).
• Experience programming in Python, ideally developing 3D applications.

Preferred:

• Interest in agent-based AI, flocking, and emergent behavior.
• Interest in cloud-based computing and web analytics.
• Familiarity with Stereovision cameras and outputs from these.
• Demonstrated skills throughout studies that can be demonstrated to Arup.
• Ability to work independently and solve technical problems with little supervision.

We're excited for you to apply!