Intern, AI-based Human-Centric Sustainable Building Design

Descripción del puesto:

Job Requisition ID #

23WD74402

Who are we looking for?
A PhD or Master's student specializing in Mechanical Engineering, Computational Architecture, or a related field. The ideal candidate should have a robust background in system-level physical modeling, simulation, machine learning, and data-driven methodologies. Proficiency in Python programming is also required.

About this Internship
Buildings account for roughly 30% of the world's total energy use and exceed 55% of global electricity consumption. The implementation of passive cooling strategies to reduce cooling loads in residential constructions can significantly reduce both energy consumption and carbon dioxide emissions in the building sector. However, the challenge is to create sustainable buildings that are not only energy-efficient but also comfortable, appealing, and satisfying from the occupants' perspective.

The effectiveness of such systems is dependent on a multitude of factors, including local climate and various design variables. This complexity often hinders architects and stakeholders from effectively incorporating passive cooling strategies into their designs. Furthermore, if occupants' needs are not considered from the design's inception, we risk creating buildings that, while technically efficient, fail to meet their comfort and aesthetic expectations.

In such instances, occupants may modify these buildings in ways that compromise their energy efficiency and negatively impact their sustainability. Recognizing the importance of early design stages, where strategies can be implemented more cost-effectively compared to later, costlier stages, our team is rising to this challenge.

We are developing a framework that merges simulation and analysis into a generative process to tackle the issue of Human-Centric Sustainable Building Design at Early Design Stages. This framework aims to facilitate the exploration of diverse building forms with high cooling performance during the early design stage, guiding decision-makers and stakeholders in the sector. Leveraging our previous work on generative design, building energy modeling, passive cooling strategies, occupant modeling, and optimization, our team at (COMPANY NAME) Research is committed to achieving this ambitious goal.

Your role may involve one or several of the following tasks:
- Enhance the energy and occupant comfort simulation workflow.
- Assist in creating a metric that integrates sustainability strategies and occupants' comfort criteria into the generative design process.
- Implement an optimization algorithm that is specifically designed for evaluating the designs.
- Develop Machine Learning algorithms to fast-track the evaluation of designs within the optimization algorithm.
- Conduct tests on the optimization algorithms under various design scenarios.

Who We Are Looking For:
A PhD or master student in the field of mechanical engineering or a related discipline. The ideal candidate will have experience in:
* Machine learning and data-driven optimization approaches.
* Physics-based modeling.
* Building energy analysis.
* Designing buildings for passive and multi-mode cooling strategies.
* Early design stages of buildings.
* Python programming.

Highly Preferred Qualifications:
· A fast learner who is eager to grasp new related topics.
· Knowledge of or familiarity with PyTorch, physics and mathematical modeling.

About (COMPANY NAME)
(COMPANY NAME) is dedicated to empowering professionals in the Architecture, Engineering, and Construction sectors, enabling them to design and create anything. The (COMPANY NAME) Design and Make Platform supports engineers, designers, and stakeholders, unlocking their innovative potential to plan, design, construct, and operate better projects.

Learn More

About (COMPANY NAME)
Welcome to (COMPANY NAME)! Amazing things are created every day with our software - from the greenest buildings and cleanest cars to the smartest factories and biggest hit movies. We help innovators turn their ideas into reality, transforming not only how things are made, but what can be made.

We take great pride in our culture here at (COMPANY NAME) - our Culture Code is at the core of everything we do. Our values and ways of working help our people thrive and realize their potential, which leads to even better outcomes for our customers.

When you're an Autodesker, you can be your whole, authentic self and do meaningful work that helps build a better future for all. Ready to shape the world and your future? Join us!

Salary transparency
Salary is one part of (COMPANY NAME)'s competitive compensation package. Offers are based on the candidate's experience, educational level, and geographic location.

Diversity & Belonging
We take pride in cultivating a culture of belonging and an equitable workplace where everyone can thrive. Learn more here: https://www.(COMPANY NAME).com/company/diversity-and-belonging