At a glance
- Opportunity
- Master's thesis
- Location
- Eindhoven; Netherlands
- Funding / pay
- Not specified by the organization
- Eligibility
- Check the qualifications in the official posting
Project description
Our VisionThe most powerful AI use cases need smart contexts, through an Intelligent Thread. A thread that connects knowledge and expertise, materialized in data, from various business functions and domains, across the full Product Lifecycle.From marketing and design, sales and operations, to delivery and service. From hundreds of ideas, thousands of designs, millions of recipes, to billions of devices. Produced in physical and digital factories. Used, out in the field, like in cars, drones, and robots.Today, knowledge and expertise across functions and domains is scattered, fragmented. Rather than viewing the Intelligent Thread as a mechanism for traceability, this project explores how it can become an active engineering knowledge and learning system.A continuously evolving foundation that provides domain specific contexts, enables deployment of AI agents, supports knowledge exchange, informed decision making, and organizational learning throughout the Product Lifecycle.Our TeamYour will join the Product Lifecycle Solutions team, an enthusiastic group of Business focused IT professionals, working from Eindhoven, Netherlands, and Bangalore, India. Operating in the global, highly competitive, highly dynamic Semiconductor industry.Stepping up to challenges in the Product Lifecycle space, enabling NXP success, at high speed. You will work from the High Tech Campus in Eindhoven. You will be able also to catch-up with master thesis students in other areas, like Supply Chain and Quality.Your AssignmentPhase 1Phase 1 focuses on understanding NXP's current Digital/Intelligent Thread and identifying opportunities to strengthen it as an engineering knowledge and learning system. Through stakeholder interviews, process analysis, and exploration of the existing PLM ecosystem, the student will investigate:How engineering knowledge and expertise flows across the product lifecycleWhich engineering artifacts, decisions, and rationale are connected, and where important knowledge gaps existChallenges in (the speed of) knowledge exchange, change management, and cross-domain collaborationOpportunities to improve how engineering knowledge is captured, connected, maintained, and reused throughout the product lifecycleThe outcome will be an assessment of the current Intelligent Thread from a knowledge and learning perspective, together with a prioritized set of research directions, that will form the basis for the master's thesis.Phase 2Building on Phase 1 findings, Phase 2 focuses to investigate one selected challenge and to design, prototype, or evaluate a concrete solution that strengthens the Intelligent Thread, as an active engineering knowledge and learning system.Possible research directions include:Engineering knowledge representation and integrationContinuous traceability and knowledge evolutionCross-domain change impact analysisCapturing and preserving engineering rationaleCross-domain engineering decision supportKnowledge discovery and reuse across the product lifecycleArtificial Intelligence, including agentic AI, knowledge graphs, or other intelligent technologies may be explored, where appropriate as enabling technologies. Nevertheless, the primary focus is on improving the Intelligent Thread as a living engineering knowledge and learning system, that supports faster and smarter engineering decision making, throughout the Product Lifecycle.Your ProfileMaster Thesis student, preferably in one the following areas:Industrial Engineering and InnovationArtificial Intelligence and Machine LearningData Science or Computer ScienceOperations and Logistics ManagementIncluding the following skills:Open, innovative and collaborative mindsetStrong analytical and problem-solving skillsStrong communication skills, navigating across cultures and functionsExcellent in English languagePython would be good to get, while SPARQL is a nice to haveOur OfferingConducting your master thesis research,based on an internship contractInteresting/challenging working environment,in a global operating companyin a highly competitive high-tech industrywith a wide variety of development and learning opportunitiesMore information about NXP in the Netherlands...#LI-3623
Funding and compensation
Compensation not specified. See the original posting for amounts, duration and conditions.
Eligibility and application requirements
Review the qualifications, research interests and required documents in the description above. The employer or university's original posting is the source for complete eligibility requirements.
Before you apply
0 of 4 readyA preparation checklist, saved on this device. The official posting determines eligibility and required documents.
How to apply
Submit your application through NXP Semiconductors's official application process. Apply early as a closing date has not been specified.
Source and listing information
This opportunity is published by NXP Semiconductors. Read the original official posting. Conditions and availability may change; confirm them with the organization. Availability verification refers to the source check, not organization endorsement.
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