Master's Thesis in Data-Efficient Hybrid Machine Learning for Reliable Vibration System Forecasting

Join Bosch Group as a Master's thesis candidate focusing on data-efficient hybrid machine learning methods aimed at enhancing the reliability of vibration system predictions. This opportunity allows you to work alongside industry experts, engage in cutting-edge research, and contribute to innovative solutions that will shape the future of predictive analytic…

Bosch Group invites applications for a Master's thesis position focused on reinforcement learning for behavior planning in automated driving. This project addresses real-world challenges in mobility by exploring advanced machine learning techniques. Project focus The thesis centers on developing and testing reinforcement learning methods to improve behavior planning in automated driving systems. The work aims to bridge research and practical application in the field of intelligent mobility. Collaboration Work closely with experts in automated driving and reinforcement learning Engage in hands-on research with direct impact on future mobility solutions Location This position is based in Renningen.

Join Bosch Group as a Master Thesis student focusing on Automated Driving Systems. This opportunity allows you to engage in innovative research and development projects that shape the future of mobility. As a part of our team, you will work closely with experienced professionals, gaining hands-on experience in cutting-edge technology.

Join Bosch Group as a master's thesis candidate to explore and develop innovative data journey solutions. This unique opportunity allows you to delve into the intricacies of data processing and analytics while contributing to cutting-edge projects that enhance Bosch's operational efficiency.

Join us at OTTO FUCHS KG, a pioneering large-scale manufacturing company, to embark on your thesis in an exciting environment where you will gain in-depth experience in the field of Data Science.Thesis Focus:Address various challenges faced by our central Data Science team, focusing on real-world, practical applications within both operational and strategic sectors of OTTO FUCHS KG while developing innovative and sustainable solutions.Extract insights from large datasets utilizing Data Science to enhance production processes or support decision-making.Develop actionable solutions using Data Science, particularly through data analysis, modeling, and visualization employing standard statistical methods and Artificial Intelligence techniques (such as Machine Learning and Neural Networks).Create a robust data foundation through Data Engineering, encompassing data integration, processing, and ETL processes on a modern cloud data platform.Engage in programming focused on Python (and SQL), applying contemporary software development methodologies.Collaborate within interdisciplinary teams alongside experts from various fields.ID: 23/114e

As part of our strategic initiative “Future Plant 2030”, we are developing a new modular platform composed of intelligent, digitally connected functional modules (Power Modules, HV Modules, Control/Communication Modules, Protection and Diagnostic Modules).We are looking for a dedicated Master's student who will conceptualize a comprehensive architecture for systems, communication, and diagnosis/monitoring as part of their Master's thesis.Master's Thesis: Design of a Modular System, Communication, and Diagnosis Architecture for High Voltage Generators (10…320 kV / up to 400 kW)This thesis is designed as a scientifically grounded project with a high practical relevance. The aim is to develop architectural concepts, evaluation criteria, and a technical roadmap – not to implement a series product.BackgroundCurrently, our systems are primarily based on monolithic structures. However, the vision for the future plant is a modular, scalable, and digitized platform, where functional blocks operate independently but coordinate effectively.Key requirements include:Flexible expandabilityIntelligent, distributed functional logicRobust internal communicationA comprehensive diagnosis and monitoring conceptThis Master's thesis integrates content originally planned as separate Bachelor and Master topics and connects system and communication architecture with diagnosis and monitoring concepts.Objectives of the ThesisDesign a comprehensive architecture for a modular high-voltage platform, consisting of:1. Digital System and Communication ArchitectureRole model: central coordination vs. decentralized module intelligenceTopology variants and communication mechanismsData and object model (process, configuration, diagnosis)2. Decentralized Diagnosis and Monitoring ConceptLocal module diagnosisSystem-wide aggregation, events, trends, and KPIsScalability, expandability, and future viability3. Evaluation & Architecture RoadmapTechnology comparisonMigrations path towards greater decentralizationPerspectives for predictive and data-driven approachesOptional:A software mockup or conceptual demonstrator (e.g., architecture or communication simulation) to visualize the developed concepts.Task Outline (Work Packages)1. Analysis & Requirements DefinitionAnalyze existing system architectureDerive key functional requirements...

Bosch Group in Renningen invites applications for a master's thesis project centered on automated driving. This research explores how imitation learning and reinforcement learning can work together to improve mobility technologies. Project focus The thesis investigates the integration of two machine learning methods: imitation learning, which enables systems to mimic human driving behavior, and reinforcement learning, which allows systems to learn optimal actions through experience. By combining these approaches, the project seeks to contribute to the next generation of automated driving solutions. Location This master's thesis project is based at the Bosch Group site in Renningen.

Join Bosch Research and merge academic brilliance with impactful industrial applications. In this Master's thesis, you will play a crucial role in crafting sophisticated anomaly detection techniques for multi-channel vision systems utilized in quality control during series production. Our aim is to develop a versatile deep-learning model that utilizes visual features to consistently identify defects across diverse products and manufacturing environments.Throughout your thesis, you will investigate innovative methods in anomaly detection and multi-channel image processing, culminating in a groundbreaking, adaptable model for quality evaluation in industrial production.You will also implement, train, and assess your model using authentic production data, ensuring its durability and relevance for industrial use.Additionally, you will collaborate closely with experts from both research and production, regularly presenting your findings to promote continuous advancements in computer vision technology for manufacturing.

Join Bosch Group as a Master's Thesis candidate focused on the optimized design of robotic assembly systems. This opportunity allows you to contribute to innovative solutions in automation and robotics, while gaining valuable hands-on experience in a leading global technology company.

Join beumergroup1 as we offer exciting opportunities for students pursuing Bachelor's, Master's, or thesis projects. This is a unique chance to engage in innovative projects and gain valuable experience in a dynamic environment.

Bosch Group in Gunzenhausen welcomes a Master's Thesis candidate interested in Quality Management. This role centers on supporting projects that improve quality standards and internal processes. Role overview The position involves working alongside experienced professionals. Collaboration is a key part of the experience, as you will contribute to ongoing quality initiatives within the organization. What you will do Assist with projects focused on enhancing quality management practices Support efforts to refine and improve internal processes Work closely with team members to achieve project goals Location This Master's Thesis role is based in Gunzenhausen.

Join us in exploring the fascinating world of Micro-Electro-Mechanical Systems (MEMS). These intricate devices, featuring mechanical structures at the micrometer scale, are essential in our daily lives, powering everything from smartphones to automobiles and smart devices. The creation of these delicate structures is a multi-stage, complex process. While causal relationships within certain production subsystems might be implicitly understood, a clear and systematic representation of these relationships is often lacking. Our project aims to model the fundamental causal truths for known subsystems and propose and validate hypotheses for the causal truths of lesser-understood subsystems.During your master's thesis, you will acquire in-depth knowledge about causality and its distinction from correlation, establishing a strong theoretical foundation for your work.You will deeply engage with MEMS technology, specific production processes, and the complexities of MEMS manufacturing.You will identify and analyze causal relationships within known subsystems, interpreting relevant variables through literature and textbooks.Subsequently, you will develop hypotheses and models for the causal truths of these systems, presenting them explicitly, analytically, and graphically.Your hypotheses will be validated through close collaboration with Bosch's expert team as you apply your developed methodologies to unknown subsystems with more complex interrelationships.You will evaluate existing algorithms for data-driven inference of causal relationships using your self-developed models.You will meticulously prepare your findings, analyze data, and regularly present results within your workgroup.

ID: REF28XAre you planning your Bachelor's or Master's thesis and looking for a company that offers practical industrial experience, solid guidance, and topics that are genuinely relevant?As a major manufacturing company with a strong focus on innovation, we provide you the opportunity to develop your thesis in one of our technical departments.The specific direction and questions will be tailored to align with your field of study and areas of interest.The goal is to generate results that add real value to our processes, technologies, and products. You will be supported by an experienced mentor from the relevant department throughout your project.This listing is open to unsolicited applications. Additionally, we regularly post specific thesis topics on our career portal.

Bosch Group invites applications for a Master’s thesis project in MEMS (Micro-Electro-Mechanical Systems) sensor technology at its Reutlingen location. This opportunity centers on research and development in MEMS sensors, which play a key role in many practical applications. What you will do Work alongside experienced professionals in the field of sensor technology Contribute to research projects that have direct relevance to real-world needs Focus your thesis on advancing MEMS sensor technology Requirements Enrollment in a relevant Master’s program Interest in MEMS sensors and their applications Willingness to collaborate and engage with a team of specialists This Master’s thesis position provides a chance to deepen technical knowledge while working on meaningful research in MEMS sensor technology.

Are you passionate about quality management and eager to dive deep into real-world applications? Join Bosch Group as a Master’s Thesis candidate in Horb am Neckar, where you will explore innovative quality management strategies that shape our products and processes. This is your chance to contribute to projects that have a lasting impact on our business and the industry.

Join the innovative team at aumovio as you embark on a master's thesis project focused on developing Metric-Guided Diffusion Models for generating high-fidelity synthetic data for in-cabin environments. This opportunity is ideal for aspiring researchers and professionals looking to dive deep into the cutting-edge field of data generation and machine learning.

Embark on a transformative journey with Bosch Group as you pursue your master's thesis focusing on the validation and optimization of controllers using advanced foundation models. This position offers you the unique opportunity to work at the forefront of innovation in a dynamic and supportive environment.

Join us at Otto Fuchs KG for a unique opportunity to undertake a master's thesis in the dynamic commercial sector. This position offers you the chance to apply your academic knowledge in a practical setting, working alongside experienced professionals who are leaders in the field. You will engage in real-world challenges and contribute to innovative solutions that drive our business forward.

Aumovio is offering a Master Thesis project based in Berlin, centered on advancing sparse 3D occupancy prediction for embedded systems. This research explores how embedded devices can more effectively interpret and model 3D environments. Project Focus The thesis aims to refine algorithms that predict sparse 3D occupancy, with a strong emphasis on adapting these methods for use on embedded hardware. The work involves applying core computer science concepts to tackle practical, real-world problems in the field of embedded systems. Key Responsibilities Improve and optimize algorithms for sparse 3D occupancy prediction Adapt and test these solutions for efficient performance on embedded devices Use computer science knowledge to address technical challenges related to 3D environment representation Location This Master Thesis opportunity is based in Berlin.

Join Bosch Group as you embark on an exciting master's thesis project focused on the development of physical Python models for drive systems in the cutting-edge field of semiconductor manufacturing. This is an extraordinary opportunity to apply your theoretical knowledge to real-world applications, enhancing your skills while contributing to innovative solutions within a globally recognized company.