As one of the most prolific innovation centers in the world, PARC offers an exceptional internship experience (a number of PARC employees also started their careers here as interns). Considered valuable members of our community, interns are fully integrated into the daily activities of PARC’s highly collaborative, multidisciplinary culture. Our interns have the opportunity to:
work with leading researchers in the physical, computer, biological, and social sciences;
engage in different stages of the research or business-development pipeline;
participate in lab meetings, presentations, poster sessions, and special programs; and
author publications and/or patents.
Please feel free to download and post this program flyer at your organization. More program information and FAQs in right sidebar. Applications are considered as they are submitted.
The Hardware Systems Laboratory at the Palo Alto Research Center (PARC) is seeking an exceptional summer intern in the field of materials chemistry to accelerate the development of novel functional materials.
BS or MS in CS, CE or related field with a minimum gpa of 3.0 with hands-on experience with building hardware systems (e.g. gaming rigs, Raspberry Pi, set-top boxes, etc.), and practical experience in robotics to participate in the development process from start to finish
BS or MS in computer science or a related field with a focus on user interface design or software engineering Hands-on expertise in software development and front-end programming. Should have working knowledge on web-based UI design and development.
Minimum cumulative GPA of at least 3.0 with familiarity or experience with Spark or Hadoop, statistics, data science and machine learning to develop one or more re-useable components using big data technology to ensure scalability to large data sets
PhD candidate in computer science or related fields with machine learning background in multi-modal data such as natural language process, image processing to Research, design and prototype novel machine learning methods
The Conversational Human-Agent Technology (CHAT) Area is looking for a graduate intern with strong web applications development skills to create a web-based user interface for a dialog system authoring tool. The tool will be used by knowledge engineers to design and create dialog system intents and language recognition rules. The intern will work closely with members of the CHAT team to deliver a high quality user experience.
Upper level undergraduate or graduate student in mechanical engineering, process engineering, chemical engineering, or applied physics. Requires experience with experimental design and knowledge of basic electromechanical systems to work on hands on experiments.
Graduate students in the fields in the fields of operations research, industrial engineering, computational and mathematical sciences with 3.0+ GPA with interdisciplinary skills also include big data analytics, modeling and simulation, and systems design to understand service operations and business processes and develop suitable abstractions for modeling and build software tools
Graduate student candidates in statistics, engineering, and computer science with strong background in optimization, statistics, machine learning, artificial intelligence to derive new algorithms for geographic disease risk spotting; and/or spatio-temporal modeling
PARC’s Self-Learning Systems project is looking for PhD candidates with experience in deep learning, reinforcement learning and optimization to develop novel learning algorithms to control autonomous systems.
Graduate student focusing on Modeling and Optimizing of Business Processes, Workflow management and Automation with strong skills with process mining, modeling software, BPMN 2.0, and a background in optimization, statistics, artificial intelligence, and programming skills to derive new algorithmic approaches in BPM for process discovery, decision management
Graduate student candidates in Engineering and Computer Science with strong background in statistics and machine learning to invent, design and prototype novel multimodal fusion engines that intelligently extract relevant information across multiple data modalities in support of decision-making tasks
Graduate student candidates in Engineering and Computer Science familiar with deep learning and strong skills with using Theano/Torch/TensorFlow or similar tools to evelop, test and validate reinforcement learning and inverse reinforcement learning algorithm
PARC invites applications from PhD students seeking summer research internships in the area of Privacy Enhancing Technologies. Interns will work on exploring and implementing practical applications of privacy-preserving technologies (such as homomorphic encryption, secret sharing, and differential privacy) for big-data analytics and machine learning.
Minimum cumulative GPA of at least 3.0 with practical experience applying statistical modeling and machine learning algorithms with real data sets to derive advanced predictive models using available data and evaluation and interpretation of developed models
Graduate students or undergraduate students completed at least 3 years of study, in Computer Science, Electrical Engineering, Mechanical Engineering with background in system modeling, monitoring, prognostics, diagnostics, machine learning, or optimization to assist in designing, developing, and delivering innovative approaches, algorithms, methods, and models as needed for system analysis, state monitoring, prediction, and recommendations
Ph.D. in statistics, computer-science with experience working on large data sets and simulation to research, design and prototype novel models based on machine learning, data mining, and statistics to solve hard analytics problems, which may range from exploratory to highly applied
Graduate student in HCI, Interaction Design, Cognitive Engineering, Psychology with Experience in creation of video and multimedia artifacts and familiarity with ethnography (work practice) to create and implement user interface designs, including initial sketches, mock-ups and working prototypes
Graduate student candidates in computer science with strong background in Machine learning as applied to personalization and recommender systems to develop techniques for building user models from data with privacy protections
M. S. or Ph.D. in computer science, electrical engineering, mathematics/statistics with experience related to developing video/image analysis technology with a focus on information and content identification and extraction to invent, design and prototype novel video analysis applications that intelligently extract relevant information from video data streams