Research Explorer Ruhr: Hosts and Application

Resource-efficient Construction
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Research Area:
The research advances information management in the building sector, focusing on AI-based methods to capture data on circular construction products and assess environmental impacts. The goal is to integrate ecological performance directly into design processes and decision-making tools. Key questions include how AI can evaluate environmental consequences of design options and embed these insights into standardized planning software. A core challenge is the lack of reliable, accessible data on material impacts such as GHG potential or deconstructability. The focus lies on linking digital planning tools (e.g., BIM) with databases like ÖKOBAUDAT, ecoinvent or INIES through modular software and trained AI models.
Further research areas include developing ecological indicators for material selection, expanding digital material libraries with life-cycle data, and studying logistics and value chains for circular construction. Furthermore resource-efficient building practices, reusable components, deconstruction strategies, and the economic viability of circular solutions are investigated. Finally, the reseach addresses societal aspects of circularity: acceptance of reused components, knowledge transfer, and enabling conditions for circular building culture.

Candidate Profile:
We seek a postdoctoral researcher whose expertise aligns with our focus on AI-supported ecological design evaluation, digital material assessment, and circular construction strategies. You should hold a completed doctoral degree in architecture, civil engineering, materials science, or a related field, and bring strong design skills combined with a solid understanding of structural or material science.
Experience in sustainability, circular economy, and resource-efficient construction is essential, as well as practical knowledge of LCA, material flow analysis, or related environmental assessment methods. Because our work develops digital and AI-driven tools linked to datasets such as ÖKOBAUDAT or ecoinvent, you should be confident using computational methods, design software (CAD/BIM), and ideally AI-based applications for planning or design optimization.
We value independent thinking, responsibility, strong communication, teamwork, and organizational skills. Excellent English skills are required.

Chair of Networked Energy-Efficient Systems
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Research Area:
We conduct high-impact, multidisciplinary research at the intersection of cloud, AI, and next-generation mobile networking, driving innovation and shaping international standards. Our work focuses on enabling intelligent, autonomous, and trustworthy networked systems that underpin future digital services. Key research themes include zero-touch telco cloud orchestration; autonomous, agile, and resilient management across the cloud continuum; advanced networking for ultra-reliable and low-latency services such as immersive services and beyond visual line of sight control of UAVs; non-terrestrial networking (NTN) for beyond-5G systems; generative AI–powered system architecture design; and secure, privacy-preserving, and trustworthy networking. Our ultimate goal is to create self-managing, adaptive, and sustainable communication infrastructures for the 6G and 7G eras.

Candidate Profile:
We seek highly motivated postdoctoral researchers with a strong background in one or more of the following areas: mobile and wireless networks (5G/6G), cloud-native architectures, Internet of things, AI-driven network management, edge and cloud orchestration, or non-terrestrial networking. Candidates should have proven research experience in mobile networking, cloud orchestration, or intelligent service management, ideally supported by high-quality publications. Experience with experimental platforms (e.g., Kubernetes, OpenStack, OpenAirInterface, or AI/ML frameworks) is a plus. We particularly value creativity, independence, and a collaborative spirit to advance multidisciplinary research bridging networking, AI, and cloud technologies. The ideal candidate will contribute to shaping autonomous, secure, and sustainable network architectures for the 6G and 7G eras.

Institute of Communications Engineering
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Research Area:
Our group works at the intersection of information theory, security, and intelligent communication systems for 6G, edge-AI and distributed computing. We study semantic and goal-oriented communications, over-the-air computation, and coding theory to enable reliable, low-latency distributed function computation in massive IoT and edge networks. We design physical-layer security and integrated sensing-and-communication (ISAC) schemes, secure MIMO-THz transmission, and statistical signal-processing methods for secret-key agreement to protect future wireless systems against powerful attackers. We also develop neural error-correcting codes and energy-/hardware-efficient learning algorithms for AI at the edge, as well as federated and multi-party computation protocols with information-theoretic and differential-privacy guarantees for correlated data. Overall, our research targets theory-grounded, practically relevant building blocks for secure, privacy-preserving and efficient 6G-class networks.

Candidate Profile:
We are looking for a highly motivated postdoctoral researcher with a solid background in information theory and/or communication theory who is enthusiastic about advancing next-generation communication and computation systems. A PhD (or near completion) in electrical or communications engineering, applied mathematics, computer science, or a related field is expected.

Components for High Frequency Electronics (BHE)
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Research Area:
Our research group works on innovative Terahertz components, and their applications in diverse areas including robotics, communication, biology and medicine. The THz components are designed and prototyped in our lab, starting with chip technology and packaging. The following research areas are involved: synthesis (epitaxy) of semiconductor structures, chip fabrication processes in our dedicated cleanroom (center for semiconductor technology and optoelectronics, ZHO), antenna and RF design of integrated THz components including 3D-EM and RF circuit design, packaging of chips into modules, and testing and modeling of THz components in our THz measurement lab. We maintain many research collaboration with groups at UDE and within UA Ruhr, as well as with a number of groups beyond UA Ruhr in Germany, and worldwide.
We are a diverse team of 10 PhD candidates, two PostDocs, and visiting scientists. Our research lab includes a cleanroom facility with a state-of-the art toolset which enables the full fabrication chain ffrom semicondutor materials to functional component modules. The department is involved in several research clusters which makes for a very lively research environment, including DFG SFB/TRR196 MARIE and terahertz.nrw, both with participation of several UA Ruhr research groups. We are also part of european research initiatives, e.g. EU JU CHIPS Move2THz, and organize a THz summer school (ITSS-TSaT). 
Our recent publications can be found on our website.

Candidate Profile:
We are looking for a motivated PostDoc in one of the areas of:

• semiconductor epitaxy, 
• advanced chip process technology, 
• RF circuit & antenna design and RF measurements
• application research and system modeling involving our THz components 

You should have gained some practical experience in one of these fields, with authored scientific publications.

Institute for Energy and Materials Processes (EMPI)
Tomography
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Research Area:
I develop 3D tomographic imaging techniques for reactive, non-reactive and two-phase flows. I combine tailored reconstruction algorithms with emission, background-oriented schlieren (BOS) and shadowgraphy measurements to resolve flow structures, refractive index fields (from which further properties such as density and temperature could be inferred) amongst others. My group pioneered BOS tomography of combusting flows, advanced ratiometric emission thermometry to 3D topographically, and introduced the TIMes method for synchronized multimodal measurements. The group performs both experimental and numerical work.

Candidate Profile:
The candidate should ideally have a good grasp of experimental work, particularly working with optics, and numerical work specifically algorithm development. Knowledge and preferrably previous experience in programming, matlab and some flow measurement methods like schlieren, shadowgraphy, emission and particle-image velocimetry to name a few are required. Furthermore, experience in image processing, camera calibration and design of experiments are advantageous.

Institute for Materials Science
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Research Area:
Our research is based on freeze casting, a well known process for producing porous materials with a controlled microstructure. An aqueous suspension is frozen and during the freezing process ice crystals grow and displace the solid particles into the interstitial spaces. After complete freezing, the solvent is removed by sublimation (freeze-drying), resulting in a porous "green body" whose pore structure reflects the morphology of the original ice crystals. Subsequent sintering gives the material its mechanical strength. With the facilities in our group and university we study the porosity, density gradient mechanical strength and flow behaviour of these samples.

Candidate Profile:
We wish to host a young a motivated person, willing to learn new science and techniques, who likes lab work and has already experience in materials science. 
They should be fluent in English. 
Knowledge of microscopy techniques is also appreciated.

Institute for Energy and Materials Processes (EMPI)
Reactive Fluids
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Research Area:

• Kinetics of nanoparticle formation and growth in gas-phase reactions
• High-temperature gas-phase kinetics and ignition properties: Shock-tube experiments
• Development of quantitative laser-based (imaging) diagnostics for reactive high-temperature flows: Concentration, temperature, particle size, flow velocity, including spectroscopic studies, photo physics modeling, optics design
• Laser-based in-cylinder diagnostics in internal combustion engines: Mixture formation, combustion progress, pollutant formation
• Nanoparticle synthesis in the gas phase: Scale up of reaction systems
• Application of functional nanomaterials in energy systems (e.g. batteries, fuel cells)

Candidate Profile:
Background in either laser diagnostics/spectroscopy or High-temperature chemical kinetics (shock tubes, flow reactors), or gas-phase synthesis of nanomaterials.