BG
Research Scientist
Bosch Gruppe
Deckenpfronn · flexible Full-time Lead Today
About the role
About
Do you want beneficial technologies being shaped by your ideas? Whether in the areas of mobility solutions, consumer goods, industrial technology or energy and building technology - with us, you will have the chance to improve quality of life all across the globe. Welcome to Bosch.
The Robert Bosch GmbH is looking forward to your application!
Responsibilities
- As a research scientist in the semantic understanding and reasoning group (CR/AIR4) at Bosch Corporate Research, you will lead and advance research on intelligent AI systems that are able to take action, reason over goals and constraints, as well as organize knowledge through complex neuro-symbolic structures.
- Your work will focus on next-generation agentic systems that combine reinforcement learning, structured reasoning, memory, and knowledge-based representations to operate effectively in semantically rich also technically demanding environments.
- This role goes beyond individual technical contributions.
- You will contribute to shaping Bosch's scientific agenda in this area by identifying promising research directions, initiating and coordinating research activities, building connections to external academic and industrial partners, as well as representing Bosch in relevant research communities.
- You are expected to bring a strong external network and effectively position Bosch in collaborative projects, scientific exchanges, also strategic initiatives related to agentic AI, reinforcement learning, as well as neuro-symbolic systems.
- From a scientific perspective, you focus on developing systems that move from passive understanding toward goal‑directed behavior.
- You investigate how agents learn through interaction, simulation, and structured feedback, represent also manipulate knowledge in compositional forms, as well as integrate reinforcement learning with symbolic abstractions, hierarchical planning, memory, and reasoning.
- Your objective is to design systems that actively act while structuring knowledge to enable robust behavior, interpretability, also strong generalization.
- You will work closely with research scientists, engineers, students, as well as domain experts across Bosch.
- In addition to conducting high-level research, you will mentor students also junior researchers, actively shape and structure collaborative research activities, and contribute to the organizational development of this research area.
- Your work will be instrumental in establishing Bosch's long-term leadership in intelligent systems for complex technical environments.
Qualifications
Education
- excellent MSc in Computer Science, Machine Learning, Artificial Intelligence, Robotics, Systems Engineering, or related fields
- PhD in Machine Learning, Reinforcement Learning, Agentic AI, Neuro-Symbolic AI, Sequential Decision-Making, or a closely related area is mandatory
- ideally several years of post-PhD research experience in academia, industry research, or a comparable environment
- strong publication record in leading AI, machine learning, or autonomous systems venues such as NeurIPS, ICLR, ICML, AAAI, IJCAI, CoRL, RSS, AAMAS, ACL, EMNLP, KR, or similar
Experience and Knowledge
- Agentic AI, RL & Action‑Oriented Systems
- strong expertise in reinforcement learning and agentic AI, including sequential decision‑making and learning‑based planning
- experience with advanced RL paradigms such as model‑based, hierarchical, offline, multi‑agent, or constrained RL
- deep understanding of goal‑directed AI systems involving memory, tool use, planning, multi‑step reasoning, and long‑horizon behavior
- ability to design and analyze systems that act in complex environments and improve through interaction, simulation, or structured feedback
- Neuro‑Symbolic Systems & Knowledge Organization
- proven experience in combining learning‑based AI with symbolic or structured representations
- familiarity with neuro‑symbolic architectures, knowledge graphs, formal reasoning structures, and compositional representations
- ability to design systems that organize knowledge in semantically meaningful ways while supporting action, planning, interpretability, and generalization
- Systems Engineering & Structured Technical Domains
- interest in applying advanced AI methods to complex technical and cyber‑physical domains such as systems engineering, robotics, or industrial automation
- experience with structured engineering artifacts (e.g. requirements, system models, simulations, or formal specifications) is an advantage
- ability to frame complex technical challenges in terms of sequential decision‑making, planning, or knowledge‑based reasoning
Scientific Leadership, Networking & Mentoring
- demonstrated ability to initiate, structure, and lead research activities in a focused technical domain
- strong external scientific network and experience building collaborations with academic and industrial partners
- proven track record in publications, project coordination, and community‑building activities
- mentoring experience with students and junior researchers, combined with strong organizational and coordination skills
AI Infrastructure & Research Prototyping
- solid experience in Python and modern deep‑learning frameworks (e.g. PyTorch, TensorFlow, JAX)
- familiarity with scalable experimentation, reproducible research, and collaborative software development
- ability to translate research ideas into functional prototypes and experimental platforms
Scientific Contributions & Mindset
- strong sense of ownership and entrepreneurial mindset in driving research topics
- ability to connect fundamental research with long‑term strategic value
- excellent analytical and communication skills, paired with a collaborative, interdisciplinary leadership style
Personality and Working Practice
- you are a scientifically strong and organizationally capable researcher with a clear ambition to shape and lead research activities in the field of agentic AI at Bosch; you combine deep methodological expertise with external visibility, mentoring experience, and the ability to build and coordinate impactful research efforts
Languages
- fluent English skills written and spoken, German is a plus
Benefits
- Work-life balance: Flexible working in terms of time, place and working model.
- Health & Sport: Wide range of health and sports activities.
- Childcare: Intermediary service for childcare services.
- Employee discounts: Discounts for employees.
- Room for creativity: Space for creative work.
- In-house social counseling and care services: Social counselling and intermediary service for care services.
The recruitment contact or superior will be happy to provide information about the individual benefit plan.
Skills
AIArtificial IntelligenceAgentic AICLComputer ScienceDeep LearningEMNLPFormal ReasoningICMLIJCAIIndustrial AutomationJAXKnowledge GraphsKRMachine LearningMulti-Agent RLNeurIPSNeuro-Symbolic AIOffline RLPyTorchRoboticsRLRSSSequential Decision-MakingSystems EngineeringTensorFlowTool Use
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