The internship positions for Summer 2021 are below:
Additional hosts and opportunities will be added during the open application period so please be sure to subscribe to our mailing list or social media channels (Facebook | Twitter | Instagram | LinkedIn) to stay up to date on news.
Please review the internship placements carefully before applying. Some programs may have specific requirements.
Click through the tabs below to view the description of each institute and its respective program(s).
Note that all internships are for 8+ week periods between mid-May and mid-August.
Gridware was founded with the belief that the passion and agility of start-up innovations will play a decisive role in the modernization of our power grid. As devastating wildfires hit communities and millions of hectares of land more frequently and more violently, a critical step in addressing this challenge and the many other challenges of climate change is the ability to bring together experts, grid operators, regulators and innovators to solve them together. To do this, we need a solution that is dynamic and deployable. A solution that is predictive and precise. A solution that stays ahead of the problem rather than catching up. We are building Gridware to be that solution.
(2 internships, 2 interns will be placed)
Supervisor: Tim Barat
Requirements:
Internship duration minimum 8 weeks, maximum 15 weeks.
Supervisor: Tim Barat
Requirements:
Internship duration minimum 8 weeks, maximum 15 weeks.
Heila Technologies is an MIT-born startup dedicated to simplifying the integration and operation of individual Distributed Energy Resources (DERs) and microgrids. Low cost, low carbon, local energy is within our reach. The Heila Platform opens the energy ecosystem to innovation and community action, making it possible to grow renewable energy-based microgrids from the ground up.
(1 internship, 1 intern will be placed)
Supervisor: Seth Drew
Heila Technologies is looking to hire a Data Scientist Intern to create and develop reports that provide insight and analysis to the customers of our control and optimization solution, thus supporting a higher adoption of low-carbon, distributed energy resources (DERs).
Responsibilities:
An ideal candidate will have a strong desire to learn and build reports in a collaborative team environment. The types of tasks you will have the opportunity to work on include:
Requirements:
Preferred/relevant majors include Statistics/Biostatistics, Mathematics, Computer Science, Data Science/Health Data Science, Engineering
The length of this internship is 12 weeks.
Founded in 2013, InTech Energy provides software solutions for utilities, energy service providers, energy evaluators and building managers to save energy and reduce costs and carbon emissions in commercial buildings as well as supporting cost effectiveness of Energy Efficiency and Distributed Energy Resource programs.
(1 internship, 2 interns will be placed)
Supervisor: Matt Bonasera
InTech is seeking to enhance the analytic capabilities of our Energy360® energy management technology (EMT)to better identify and quantify changes in building equipment and energy use operations due to non-routineevents, anomalies, or planned energy efficiency projects. The goal is to implement a minimally intrusive data collection process that uses building meta-data (size, usage, HVAC system type, etc.), weather data, and theprimary utility meter data, and minimal additional energy monitoring or sensoring, that can be used on individual buildings, i.e., we are not seeking a population-based analysis.
The anticipated role is a combination of data science and an understanding of the physical nature of building operations. The data scientist would access InTech’s and other historical building energy usage databases (US Dept. of Energy, US Energy Information Administration, Energy Star, Utility studies, Electric Power Research Institute studies, etc.) to discover patterns for normal and abnormal energy consumption that can be repeatedly used in analyzing, measuring and forecasting energy use in buildings.
Requirements:
Strong background in creative data analyses, and working with large data sets using a variety of techniques to solve a real-world problem. Must have practical experience in scaling creative solutions for production scale in a software product environment. Experience can be shown with class projects or independent projects. Education in Data Science and related areas would be very helpful.
Other preferred qualifications:
The ideal candidate will also understand the basic physical nature of building operations, e.g. understanding how factors like weather, building usage, and building occupancy influence energy consumption.
At Johnson Controls, we transform the environments where people live, work, learn and play. From optimizing building performance to improving safety and enhancing comfort, we drive the outcomes that matter most. Dedicated to protecting the environment, we deliver our promise in industries such as healthcare, education, data centers, and manufacturing.
(1 internship, 3 interns will be placed)
Supervisor: TBD
We will be looking to have interns assist on several projects that will help us expand the offering of a SaaS based application that provides visibility and improvement into the performance of buildings and facilities. Buildings consume 40% of the overall energy in the world. Our applications help to improve the performance of facilities while improving the experience of the occupants in these spaces. We are looking to expand the value proposition of our offering and we are looking for assistance across the areas below:
Requirements:
Internship duration: 10-12 weeks, starting May or June (flexible)
Berkeley Lab is a member of the national laboratory system supported by the U.S. Department of Energy through its Office of Science. It is managed by the University of California (UC) and is charged with conducting unclassified research across a wide range of scientific disciplines. Located on a 202-acre site in the hills above the UC Berkeley campus that offers spectacular views of the San Francisco Bay, Berkeley Lab employs approximately 3,232 scientists, engineers and support staff.
(5 internship positions, 5 interns will be placed)
Machine learning (ML) models have demonstrated excellent performance in optimizing building controls for energy efficiency and demand flexibility. However, transfer learning is a challenge in ML based building controls as a very limited number of buildings have adequate and good-quality data for training and validating ML models. Transferring these ML models to other buildings with limited data will require effective algorithms which are structured in a way that bridges two different buildings capturing their common and different characteristics (e.g., energy system type, operation strategies, climates). The intern will help review transfer learning algorithms and choose a few to test for reinforcement learning based building controls. One intern is needed.
The intern is required to have knowledge of machine learning especially reinforcement learning and understand transfer learning. It is a plus if the intern knows how to use popular ML toolkits for Python coding and testing ML models. The intern will be part of a project team presenting and discussing progress weekly. Depending on the outcomes, there is a potential for the intern to contribute to the writing of a journal article.
Work location: LBNL main campus (assuming COVID-19 is over by the summer - if not then some/all work may become remote).
Working period: 8 weeks
Preferred start date: flexible start from mid May to early July of 2020.
The Applied Energy Materials group at ESDR is looking for one materials sciences intern. The intern will perform experimental materials research on solid-state battery for electric vehicle applications. The intern will synthesis new solid-state ion conductors, fabricate batteries based on those ion conductors, and testing the battery cells.
This is an experimental internship.
Work location: LBNL main campus in Building 70 (assuming COVID-19 is over by the summer - if not then some/all work may become remote).
Preferred start date: beginning of summer.
New materials with tailored functionality are needed for renewable energy technologies. Membranes enable the selective transport of specific species are critical components in these technologies, for example, the proton conducting membrane in a hydrogen fuel cell. Membranes made of polymers are attractive due to their tunable chemistries and favorable mechanical properties. However, we still need to better understand how molecular architecture dictates the nanoscale assembly of polymer molecules and ultimately membrane performance. This internship will focus on probing the nanoscale structure of membranes using unique experimental X-ray tools coupled with simulations and other characterization methods to gain new insights into membrane structure-property relationships. The work will involve working closely with research groups at Berkeley Lab and take advantage of Berkeley Lab's world-class facilities, including the Advanced Light Source and the Molecular Foundry.
Number of interns required: 1
Work location: LBNL main campus (assuming COVID-19 is over by the summer - if not then some/all work may become remote).
Preferred start date: dates flexible during the summer of 2021
We seek one motivated undergraduate intern to contribute to the development of a new chemical imaging method to optimize biofuel production in bioreactors. The candidate will work with a multidisciplinary team of scientists in Earth & Environmental Sciences and Biosciences Divisions at Lawrence Berkeley National Laboratory (LBNL). Our groups are collaborating on using quantum sensing and complementary methods to study microbial metabolic processes, ultimately for the in-situ observation of single-cell biochemistry. Depending on background, and onsite or virtual intern, the candidate will design optical, microfluidics or microwave instrumentation, develop python software for data acquisition, or acquire and process chemical imaging data from microorganisms using a diamond-based quantum sensor, a confocal fluorescence microscope or a Raman microscope.
Motivated candidates from the core STEM fields will be considered, and preference will be given to the ones with relevant experiences and skills.
Work location: LBNL main campus (assuming COVID-19 is over by the summer - if not then some/all work may become remote).
As our infrastructure systems, novel and scalable decision-making methodologies are needed to resolve the 1) interdependency among different systems, and 2) interactions with the complex climate events, e.g. the wildfire, within the planning and operation problems. One intern is expected to assist the existing LDRD projects.
Basic programming and data analytic skills are required. Candidates with experience in economics, machine learning, optimization are preferred.
Work location: work from home is expected.
PingThings offers the world’s fastest time series data management, analytics, and AI platform for engineering, industrial, and scientific applications with a core focus on electric utilities.
PingThings is excited to offer multiple internship opportunities to support a major, 3-year ARPA-E funded project called “A National Infrastructure for Artificial Intelligence on the Grid”, or NI4AI (www.ni4ai.org). PingThings seeks to advance the state of the art by deploying a large number of high frequency sensors on the electric power grid. These sensors will collect open access data that researchers and other innovators may use to develop next-generation AI/ML tools to improve the safety, reliability, and sustainability of the grid. The sensors have been demonstrated to support applications such as wildfire mitigation, system monitoring, and renewables integration. The project provides access to the data via PingThings’ PredictiveGrid platform (https://pingthings.io/platform.html) to make it easier to access and analyze data, and work with collaborators. Our goal is to eliminate barriers that have historically made it difficult to develop and deploy tools that use big data for power systems applications.
Internship opportunities span the spectrum from the intensely technical (power and electrical engineering, computer science, mathematics) to the organizational, business, and marketing sides of the project.
(6 internship positions, 6 interns will be placed)
Are you organized? Detail oriented? Help with an array of project management tasks to coordinate across a cross functional team of software engineers and data scientists. You will help a team of world-class engineers achieve their objectives and will help us to set up and maintain outreach materials to communicate with key project partners -- in industry, government and academia – about the work we are doing. Your attention to detail will ensure that you are a critical part of keeping the team on track to implement new capabilities and achieve project goals.
Requirements
Strong organizational skills.
Attention to detail and project management practices.
Strong science and technical communication skills.
Ability to flourish in a remote environment.
Positive attitude, empathy, self-awareness, and a desire to continually improve.
Are you interested in helping a startup effectively communicate how its technology can help change and save the world?
REQUIREMENTS
Strong organizational skills.
Strong writing and marketing skills
Strong science and technical communication skills.
Ability to flourish in a remote environment.
Positive attitude, empathy, self-awareness, and a desire to continually improve.
The National Infrastructure for AI project is synthesizing terabytes of time series data from previously collected sources and from sensors deployed in the field into a single platform where data can be more easily found, accessed, and analyzed. We need help finding, collecting, organizing cleaning, and ingesting these data. This role will help you build data management skills that are foundational for anyone who aspires to work with real-world data to develop.
Requirements
Majoring in EECS, Engineering, Mathematics, Physics, or a related field.
Familiar with Python (numpy, pandas, matplotlib).
Inquisitive mind.
Strong communication skills, a positive attitude, and empathy.
Self-awareness and a desire to continually improve.
Use your knowledge of JavaScript (react.js and D3.js), HTML, and CSS to improve our web client, a complex in-browser application relied upon by users every day. You will work with real-time data streams, engineer for performance across browsers, and delight people by making the best software we can imagine. You will collaborate closely with stakeholders to spec, build, test and deploy new features.
Requirements
Working toward a degree in Computer Science, Engineering, or a related field, or equivalent training, fellowship, or work experience.
Experience with our stack: React, D3.js, Jest, GraphQL, node, Docker, etc.
1+ years of experience writing client-side JavaScript
Expertise in building complex layouts with CSS and HTML
Experience building and debugging complex systems in a team environment.
Experience with modern browser technologies.
Experience designing web sites and applications.
Strong UX and design sensibilities, and a desire to sweat the small stuff.
Strong communication skills, a positive attitude, and empathy.
Self-awareness and a desire to continually improve.
If you think of programming as a tool to accomplish a wide variety of tasks and Python is your tool of choice, then this internship is for you. Help our engineering team develop and maintain our backend systems, create simple web applications and APIs, and wrangle and analyze datasets. You will work with systems engineers, data scientists, and web application developers to automate and improve our workflows and solve data-related challenges.
Requirements
Working toward a degree in Computer Science, Engineering, Mathematics, Physics, or a related field, or equivalent training, fellowship, or work experience.
Software engineering experience
Strong communication skills, a positive attitude, and empathy.
Self-awareness and a desire to continually improve.
Use you experience developing AI/ML data analysis pipelines to implement develop state-of-the-art algorithms for extracting meaningful insights from large volumes of time series data. You’ll collaborate with our software engineering and data science teams, as well as research partners to develop algorithms showcasing how our state-of-the-art time series data platform can support AI/ML tools for modernizing the electrical grid. For the right candidate, this position could lead to an original research publication.
Requirements
Working towards a degree in EECS, Engineering, Mathematics, Physics, or a related field.
Prior coursework in machine learning, signal processing, or power engineering.
Experience with machine learning, software engineering or data science workflows, and familiarity with Python (sklearn, numpy, pandas, matplotlib, etc.).
Interest in reviewing academic literature.
Inquisitive mind.
Attention to detail.
Strong communication skills, a positive attitude, and empathy.
Self-awareness and a desire to continually improve.
Takachar is an MIT spinout company with a test site in Berkeley, CA. The company's vision is to expand the amount of biomass (crop and forest residues) economically converted into useful products (we turn trash into cash). Our impacts include income and job creation in rural areas, as well as mitigation of CO2 emission and air pollution associated with conventional open-air biomass residue burning. If successful, this could also potentially reduce the risk of catastrophic wildfires.
(1 internship, 1 intern will be placed)
Supervisor: Kevin Kung
In summer 2021, we will be building and testing an internal prototype. We are seeking one project engineer to coordinate this effort. The engineer will assist in testing the prototype, first in a laboratory setting, and also potentially in the field. In the latter stage of the project, you should be prepared to work in a rural environment (in California) under resource-constrained settings.
Requirements:
Prior experience with SolidWorks, design for manufacturing, control systems, and reactor testing will be helpful. A project website (if you have one) will help us gauge your experience.
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