Home › Companies › Cellumation › PhD Researcher - (DC4) Hybrid Learning Control for Agent-Based Intralogistics Systems - CAVECORE (m/w/d)
PhD Researcher - (DC4) Hybrid Learning Control for Agent-Based Intralogistics Systems - CAVECORE (m/w/d)
Cellumation · Bremen Kleiner Ort 5 · Hybrid · Active · Personio
Job facts
| Field | Value |
|---|---|
| Company | Cellumation |
| Title | PhD Researcher - (DC4) Hybrid Learning Control for Agent-Based Intralogistics Systems - CAVECORE (m/w/d) |
| Normalized title | - |
| Department / team | Software Engineering / Software Engineering |
| Location | Bremen Kleiner Ort 5 |
| Work model | Hybrid / Hybrid |
| Employment type | Full Time |
| Salary | - |
| Status | active |
| ATS provider | Personio |
| Posted / first seen | 2025-09-22 / 2026-05-30 |
| Changed / last seen | 2026-05-30 / 2026-06-06 |
Related slices
| Page | What it contains | Open |
|---|---|---|
| Company jobs | Active postings from Cellumation. | Open |
| Company breakdowns | Role, location, ATS, and work model facets for this company. | Open |
| ATS provider jobs | Active postings observed through Personio. | Open |
| Provider filtered search | The same provider as a filtered job collection. | Open |
| Department jobs | Active postings in Software Engineering. | Open |
| Work model jobs | Active Hybrid postings. | Open |
| Lifecycle events | Open, update, close, and reopen events for this posting. | Open |
| Original posting | Canonical source or apply URL captured from the ATS. | Open |
Linked records
| Company | Cellumation |
| Source | 768aed21-6d13-4ce7-bf12-f2d8604d916b |
| ATS provider | Personio |
Description
Your mission
You will research and develop innovative, hybrid machine learning control systems for use in the Celluveyor system. The exact research focus will be determined jointly during the first year of the project. You will implement, integrate, test, and validate the developed algorithms on real production systems as well as on hardware and embedded software platforms. You will analyze and optimize control strategies for intelligent, modular conveyor systems using modern methods from machine learning and automation technology. You will conduct scientific research, publish research results at international conferences and in academic journals, and write your dissertation as part of your work. You will participate in training sessions, international research stays (secondments, e.g., in Bielefeld and York), as well as networking and exchange activities within the project. You will work closely with industry partners and academic institutions within a European research network and contribute your results to joint projects.
Your profile
You hold a master’s degree (or equivalent) in computer science, engineering, robotics, or a related field. You meet the MSCA eligibility requirements: a maximum of four years of research experience following your master’s degree and no completed doctoral degree. You have excellent programming skills in C++ and Python, as well as experience in developing complex software systems. You bring in-depth knowledge of machine learning, (multi-agent) path planning, robotics software (e.g., ROS2), and simulation techniques. Ideally, you have some experience with embedded software or hardware-related development; knowledge in the field of intralogistics is a plus but not a requirement. You quickly familiarize yourself with new topics and are interested in interdisciplinary issues at the intersection of machine learning, control theory, and robotics. You work in a structured, independent, and self-directed manner and are motivated to develop your own research focus areas and publish scientific papers. You can analyze complex problems and drive solutions from research through to practical implementation in real-world systems. You communicate clearly and enjoy collaborating with industry and research partners in international and interdisciplinary teams. You have excellent written and spoken English skills. You are open to international mobility (e.g., research stays abroad) as part of the project.
Important requirement:
Early-career researchers: At the time of hire, you must be in the first four years of your academic career and not yet have earned a doctoral degree. Mobility rule: In the three years immediately preceding your start date, you may not have resided in Germany or carried out your primary activity (work, studies, etc.) there for more than twelve months. For applicants outside the EU: You must apply for a work visa for Germany/the EU; therefore, additional requirements (language certificates, etc.) may be necessary.
Why us?
Diversity : Because we’re a diverse team: We’re young, we’re old, we’re international yet proud of our local roots, we’re tinkerers, we’re all-rounders, we’re experts. You’re more than welcome! Team Spirit : Here you’ll find flat hierarchies, room for ideas, and—if you’re up for it—group barbecues or other events. Development : We place great value on progress and development—we want not only to grow as a company, but also for you to grow with cellumation. That’s why we support you in your potential-oriented development and professional training. Equipment : Here, you’ll be equipped with state-of-the-art hardware and work in bright, quiet office spaces. And of course, there’s always coffee! Health : Your health is important to us. That’s why we provide ergonomic office equipment, such as height-adjustable desks. Thanks to our company fitness program, you can stay active after work at a location that suits you. Flexibility : We offer flexible working hours, 30+ days of vacation, and the option to work remotely.
Kontakt
Recruiting-Team
[email protected]
+49 421 331135 40
Full job record
| Job ID | 16c2060ca8553bb8ed7b6b2a34c54f784351beea |
| Org ID | c672fb02-023e-44e0-9861-4585d4db8aa6 |
| Source ID | 768aed21-6d13-4ce7-bf12-f2d8604d916b |
| Board ID | 768aed21-6d13-4ce7-bf12-f2d8604d916b |
| Provider | personio |
| Provider Job Key | 2353617 |
| Title | PhD Researcher - (DC4) Hybrid Learning Control for Agent-Based Intralogistics Systems - CAVECORE (m/w/d) |
| Normalized Title | — |
| Status | active |
| Active | yes |
| Location Text | Bremen Kleiner Ort 5 |
| Department | Software Engineering |
| Team | Software Engineering |
| Employment Type | full_time |
| Workplace Type | hybrid |
| Remote Policy | hybrid |
| Country | Bremen Kleiner Ort 5 |
| Region | — |
| City | — |
| Salary Raw | — |
| Salary Min | — |
| Salary Max | — |
| Salary Currency | — |
| Salary Period | — |
| Source URL | https://cellumation.jobs.personio.de/job/2353617?language=en |
| Apply URL | https://cellumation.jobs.personio.de/job/2353617?language=en |
| First Seen At | 2026-05-30 05:55:22Z |
| Last Seen At | 2026-06-06 07:55:57Z |
| Last Checked At | 2026-06-06 07:55:57Z |
| Last Changed At | 2026-05-30 05:55:22Z |
| Inactive At | — |
| Source Posted At | 2025-09-22 08:30:35Z |
| Source Updated At | — |
| Raw Payload Uri | s3://job-postings-prod-raw-590183727216/raw/provider=personio/board=cellumation.de/date=2026-06-06/2026-06-06T07-55-57-440Z-a62442af8d03b7d146fc104ebbc8baf91377e2b0f39f01030299fadb00f58cad.json |
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