Research Explorer Ruhr: Hosts and Application (Engineering Sciences)

Here you find the profiles of the participating professors in the Engineering Sciences. You can conveniently apply directly at the end of each profile: please download and fill in the application form and send it to us via e-mail (use the blue button at the end of the PDF form). Please keep in mind to attach your CV and a publication list to the e-mail. The application deadline is 1 March 2020.

Important note: In case you would like to work with a researcher who has not uploaded a profile, please send your application to research-explorer@rub.de so that we can get in touch with the respective professor. Do NOT send any kind of application to a professor directly.

Civil Engineering:

Prof. Dr. Carolin Birk (University of Duisburg-Essen)

Faculty of Engineering, Department of Civil Engineering

Structural Analysis of Plates and Shells

Research Area:

Research in the group of "Structural Analysis of Plates and Shells" at the University of Duisburg-Essen focusses on the development of robust and efficient numerical simulation techniques for solid mechanics and coupled problems with a particular focus on time-dependent problems. We are employing and developing the scaled boundary finite element method (SBFEM). This semi-analytical technique excels in modelling radiation damping and singularities and facilitates the use of structured meshes in the context of image-based analysis.

Our main research interests include:

  • Dynamic soil-structure interaction
  • Seismic wave modelling
  • Structural acoustics
  • Numerical modelling of wave-based methods for non-destructive testing and parameter identification
  • Image-based mesh generation and analysis with applications to material modelling and computational homogenization
  • Damage and fracture modelling, thermally-induced crack propagation
  • Non-classical discretization methods for thin-walled structures, solid mechanics and coupled problems

Candidate Profile:

The ideal candidate has obtained a PhD in an area related to the above fields of interest. He or she has a strong background in computational mechanics and can demonstrate very good programming skills. A track record of publications in high-quality international journals would be an advantage.

Host's Website

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Computer Science:

Prof. Dr.-Ing. Steffen Bondorf (Ruhr-Universität Bochum)

Center of Computer Science

Distributed and Networked Systems

Research Area:

The Distributed and Networked Systems (DNet) group is part of the Center of Computer Science – a joint center of the faculties of Mathematics and Electrical Engineering – at Ruhr-Universität Bochum. Every distributed computer system relies on a some kind of networking technology to connect its subsystems. If such a distributed system is responsible for executing a safety-critical task, e.g., brake-bywire in a modern vehicle or process control in a factory, then the underlying network needs to fulfill deterministic performance demands. That is, certain strict bounds on the end-to-end delay of messages must not be violated under any circumstances. In the DNet group, we are interested in formal verification of such deterministic networking technologies. Our activities thus span the entire stack of
tasks that are required to obtain said delay bounds - from system modeling to performance analysis - and we specialize in the Network Calculus framework.

Candidate Profile:

A matching Research Explorer Ruhr candidate to join the DNet group should possess a background in computer science, mathematics and/or electrical engineering as well as an intrinsic motivation to work on hard problems. More precisely, a candidate should be interested in theoretical and applied computer science, foremost in the areas of computer networks, queueing systems and realtime
systems, to take on open challenges in the Network Calculus framework that are uncovered by modern technologies, standards in development as well as requirements of novel distributed applications. An interest in other formal verification techniques besides Network Calculus (such as model checking) as well as accompanying performance evaluation metrics like simulation and measurement
are a plus. Programming skills are also indispensable for performance evaluation.

Host's Website

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Prof. Dr. Jian-Jia Chen (TU Dortmund University)

Informatik 12: Computer Engineering & Embedded Systems

Design Automation for Embedded Systems

Research Area:

Informatik 12, at the faculty of computer science, is responsible for the entire education and most of research for embedded systems and computer engineering. Embedded systems are defined as information processing systems embedded into a surrounding technical product. This includes information processing systems in vehicles (cars, airplanes etc.), in smart buildings, in consumer electronics and industrial automation. After reorganization of all offices by use of information processing, an equivalent influence on all technical systems is expected. Informatik 12 wants to enable students to evaluate and develop embedded systems. Moreover, students should be able to understand and use platforms on which computer science-specific applications are developed. In addition, Informatik 12 wants to increase knowledge in the domain of embedded systems by research contributions and also utilizes this knowledge in specific projects.

The current active research directions and projects can be found in https://ls12-www.cs.tu-dortmund.de/daes/en/research.html. Two potential projects for the visiting scholars can be found below:

  • Data analysis on resource-constrained systems, as part of the collaborative research center SFB876, which brings together data mining and embedded systems. On the one hand, embedded systems can be further improved using machine learning. On the other hand, data mining algorithms can be realized in hardware, e.g. FPGAs, or run on GPGPUs. The restrictions of ubiquitous systems in computing power, memory, and energy demand new algorithms for known learning tasks. These resource bounded learning algorithms may also be applied on extremely large data bases on servers.
  • Design and optimization of non-volatile one memory architecture: Different forms of non-volatile memories (NVMs) have been introduced in the past decades. The recent development of NVMs has led to a promising future for building extra low-power computing systems when a NVM device is used as the media of both main memory and storage at the same time. However, most of the existing research results and system designs still consider NVM devices as additional memory or storage. Our project intends to provide the fundamental cornerstone of one-memory architectures that can be used to enable normally-off computing and improve battery-driven embedded systems. Our project aims to enable the effectiveness of one-memory architectures by performing design-space exploration in hardware and software designs, and by integrating analytical as well as optimized resource management in operating systems.

Candidate Profile:

The candidates who electronical engineering, computer engineering, or computer science background are welcome to join my group. The skills needed are programming languages (C, C++, Python, or Java) and algorithm design/analysis. For the NVM project, the knowledge of computer architecture is definitely a benefit. For the data analysis project, the knowledge of machine learning algorithms and programming skills in python or R are expected.

Host's Website

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Electrical Engineering and Information Technology:

Prof. Dr. Timm Faulwasser (TU Dortmund University)

Electrical Engineering and Information Technology

Institute for Energy Systems, Energy Efficiency and Energy Economics

Research Area:

Our research is on new methods for control and optimization of networked systems subject to complex nonlinear dynamics, uncertainties and constraints. In terms of applications we focus on multi-energy systems, power systems and climate economics.
In terms of method development we work on

  • nonlinear model predictive control,
  • optimal control,
  • applications of machine learning to dynamic systems,
  • distributed numerical optimization, and
  • uncertainty quantification.

Our research is located in the transdisciplinary overlap of systems and control, optimization and energy systems.

Candidate Profile:

We are looking for highly motivated and quality driven candidates who are interested in pushing the frontiers of control and optimization of dynamic systems.
Successful candidates should have a strong background in systems and control and/or optimization. In particular it is beneficial if you are familiar with model predictive control and or stochastic optimization methods.
Previous experience with energy or power systems is not a definite must but an important plus.
We expect strong team playing and communication skills. Working language in our team is English. Ideal candidates pair scientific creativity and curiosity with strong technical/mathematical skills.
You will join a young and impact driven team that competes successfully and internationally in terms of scientific progress.

Host's Website

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Prof. Dr. Martin Hofmann (Ruhr-Universität Bochum)

Electrical Engineering and Information Technology

Photonics and Terahertz Technology

Research Area:

Our research areas are:

  • Optoelectronic Devices, in particular Diode Lasers (e.g. Spin-controlled Lasers, femtosecond Diode Lasers)
  • Semiconductor Spectroscopy (e.g. Optical Gain in new Semiconductor Materials, time-resolved ultrafast Spectroscopy)
  • Diode Laser Systems for new Applications (e.g. Femtosecond Lasers for Two-photon Polymerisation)
  • Terahertz Technology (systems, applications, spectroscopy, machine learning & classification)
  • Optical Imaging (Optical Coherence Tomography, Digital Holography, Confocal Microscopy, Photoacoustic Imaging for Biomedical Applications and Nondestructive Testing)

Candidate Profile:

The perfect candidate has expertise and interest in one or several of the above mentioned research areas.
Additional complementary expertise (e.g. in device design and processing, numerical modelling, THz applications or optical imaging) would be perfect.

Host's Website

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Mechanical Engineering:

Prof. Dr. Marcus Grünewald (Ruhr-Universität Bochum)

Thermo and Fluid Dynamics

Laboratory for Fluid Separations

Research Area:

At the laboratory for fluid separations, we are working on different research areas: absorption and multiphase flows, reaction engineering, process design and flexible apparatuses. In all research areas, we are focusing on the implementation of new measurement techniques to acquire different state variables or hydrodynamic phenomena within the apparatuses. Where possible we combine experimental measurement techniques with multidimensional modelling and new evaluation methodologies. We have a chemical lab as well as a larger facility to perform experiments in our technical columns.
or example, we are using a fiber optic temperature measurement system to acquire the temperature profiles within tube reactors for heterogeneously catalyzed gas phase reactions. Combining experimental results with continuous reactor models give us a further insight in heat transport effects within the reactors. In another example regarding multiphase gas-liquid systems, we are using a wire mesh sensor to get insight in the phase distribution in the cross sections. Together with adequate models, we develop methodologies to improve the scale-up.

Candidate Profile:

Seeking for or holding a doctoral degree in chemical engineering, process engineering or systems engineering.
Experience in mathematical modeling as well as dynamic and steady state simulation in chemical engineering (in particular unit operations or chemical reactors).
Experience in optimization for chemical engineering systems.
Experience in performing experiments in the lab involving process equipment.

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PD Dr. habil. Rebecca Janisch (Ruhr-Universität Bochum)

Interdisciplinary Centre for Advanced Materials Simulation (ICAMS)

Working Group Mechanical Properties of Interfaces

Research Area:

The working group "Mechanical Properties of Interfaces" investigates the mechanical properties of microstructures in metals with atomistic simulations (molecular dynamics simulations, ab-initio density functional theory based calculations). Our goal is to understand the fundamental properties of grain and phase boundaries based on their atomistic and electronic structure. Based on this understanding, we derive scale-bridging descriptions of the effect of internal interfaces on deformation and fracture of microstructures.

Candidate Profile:

The candidate should have experience in ab-initio calculations and/or molecular dynamics simulations and a strong interest in investigating cohesion, deformation, and fracture of interfaces in metals and alloys.

Host's Website

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Prof. Dr. Alfred Ludwig (Ruhr-Universität Bochum)

Institute for Materials

Materials Discovery and Interfaces

Research Area:

The chair “Materials Discovery and Interfaces” is developing new multifunctional materials by using combinatorial deposition processes (material libraries) and high-throughput characterization methods. The created multidimensional datasets enable data-driven materials discoveries and support efficient optimization of newly identified materials, using combinatorial processing. Furthermore, these datasets are the basis for multifunctional existence diagrams, comprising correlations between composition, processing, structure and properties, which can be used for the design of future materials. Furthermore we are working in the field of software developing for data analysis, data visualization and interactive display of data, coupled with the implementation of AI strategies (e.g. machine learning methods) in current research workflows. Another focus is laid on automated data retrieval from the measurement stands, to improve the data management and the implementation of the feedback loop between the experiments and the data analysis.

Candidate Profile:

We are looking for a researcher, with a background in material science, who likes programming and who is interested in developing new strategies for accelerated scientific discoveries. It would be beneficial if the person already has some practical experience in developing data analysis software (preferably Python) and some practical experience in developing and using machine learning techniques.

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Prof. Dr. Christof Schulz (University of Duisburg-Essen)

Institute for Combustion and Gas Dynamics

Reactive Fluids

Research Area:

Understanding and controlling combustion processes and the synthesis of nanomaterials in the gas phase is at the center of research of our work. Nanoparticles with tailored properties are synthesized in flames, plasmas, and wall-heated reactors in the nanomaterials synthesis team. The work is aimed at the development of new materials, in particular for use in energy technologies. Research also includes laser-based techniques for in situ measurements of concentration, temperature, droplet and particle size as well as velocity in reactive flows. The laser diagnostics team conducts fundamental research on new measuring techniques. These techniques are also employed in the internal combustion engines team that uses engine test cells that are equipped for optical in situ measurements to shed light on in-cylinder processes. The kinetics team uses shock tubes to investigate rates and reaction mechanisms in combustion, ignition, and particle formation. By coupling shock-tube reactors with optical and mass spectrometric measurement technology it is possible to investigate ultra-fast processes at high temperatures in the gas phase.
In addition to publicly funded fundamental research, these topics are also being addressed in collaboration with numerous partners from industry. These investigations are directed towards materials synthesis, practical combustion in piston engines and gas turbines, petro-chemistry, and the development of measurement strategies.

Candidate Profile:

Scientist with background on nanoparticle aerosol diagnostics using optical methods that also has a good understanding of the particle and its environment (e.g. concerning evaporation, energy accommodation, plasma formation). Analyzing measurement methods with statistical methods. Alternatively, the theoretical toolbox to analyze experimental data is helpful (i.e. experimental skills are not a crucial requirement as long as previous analysis of experimental data is demonstrated).

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Prof. Dr. Doris Segets (University of Duisburg-Essen)

Institute for Combustion and Gas Dynamics

Process Technology for Electrochemical Functional Materials

Research Area:

Research in the group on Process Technology for Electrochemical Functional Materials, led by Doris Segets, focuses on the dispersion and ink formulation of nanoparticles for their large-scale coating on flexible substrates. We are striving for energy applications and sustainable technologies including batteries, fuel cells, and (opto)electronics.
Starting from the high-performance nanomaterials synthesized at UDE’s NanoEnergieTechnikZentrum (NETZ) in large quantity, we develop a knowledge-based formulation of functional inks and their subsequent coating as (nano)structured layers. To realize this vision, we make use of a toolbox we already developed for the in-depth characterization of colloidal interfaces at the molecular level.
By using appropriate descriptors, we connect the therefrom-gained findings with information on dispersibility and colloidal stability at the particle level. Such in-depth understanding of disperse ink properties is then the starting point for the preparation of tailored coatings. Finally, we link layer properties of these coatings with electrode performance. Due to hierarchical knowledge-transfer along the design chain, our approach is an enabling technology for true product design, exemplified by means of electrochemical functional materials.
The highly international, interdisciplinary Segets Group is embeded in a strong (inter)national network, with collaboration partners in Germany and Europ but also in the US, Japan and China. Our visiblity is also reflected by several Prices and Awards (e.g., the Friedrich-Löffler-Price 2016), our activities in professional ProcessNet or Editorial board Membership (Reaction Chemistry and Engineering)

Candidate Profile:

Applicants have a strong background either in the processing and characterization of electrochemically active, functional materials as the are used for battery and/or fuel cell electrodes, or in the field of chemical Engineering, in particular particle science and Technology. Expertise can be both, experimentally or theoretically. Also applicants with a Background in chemistry or materials science are suitable in case they have experience in colloid science and nanoparticle processing.
With regard to fields of application, These can expand from battery and fuel cell electrodes over photocatalytically active materials and quantum dots down to fundamental aspects of nanoparticle processing including (continuous) Synthesis, nanoparticle separation and dispersion. Also contributions from the field of automation, high-throughput experimentation and machine learning are thinkable as these can be a linker to the methods applied in our team.
Applicants have made outstanding contributions during their PhD and are able to conduct independent research. Moreover, they are able to integrate into our highly international, cross-disciplinary team.

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Prof. Dr. Frank Walther (TU Dortmund University)

Materials Test Engineering

Research Area:

Fatigue Testing, mechanical testing, in-vitro fatigue testing of bioimplant materials, micro magnetic characterisation, in-situ testing, microscopy and microanalysis, in-situ electron microscopy

Candidate Profile:

Our team look for a candidate with strong background in material science and physics reflected in publications in peer-reviewed journals.

Host's Website

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Spatial Planning:

Jun.-Prof. Dr. René Westerholt (TU Dortmund University)

Spatial Modelling Lab

Research Area:

The newly established Spatial Modelling Lab is committed to research in the nexus of geoinformatics and quantitative human geography. The lab forms an integral methodologically oriented part of the Faculty of Spatial Planning offering a range of interesting applications in various planning-related topics. The two main research areas are the statistical spatial analysis of user-generated geographic data, and place-based GIS. Both topics are relevant not only in terms of state of the art methodological and conceptual basic research, but also for applications in spatial planning where considering the human factor is crucial. The focus on quantitative and formal approaches to the investigation of data from and about people in the planning context puts the laboratory in a unique position both nationally and internationally.
Our contemporary society produces an unprecedented amount of data. This data captures fractions of our everyday lives, and many datasets are also of a geographic nature. One recent trend that has been enabled and facilitated by the widespread use of location-enabled and connected devices is the paradigm of the ‘produser’. Users are no longer passive consumers but also producers of vast amounts of data at the same time. User-generated geographic datasets thereby differ from more established authoritative or scientific counterparts. Their complex provenance implies heterogeneous underlying data-generating processes affected by subjectivity, autonomous behaviour, and cognition-induced effects. These effects need to be addressed by spatial analysis routines, because they otherwise affect the characteristics of statistical estimators and models leading to a potential disclosure of spurious phenomena and patterns. Investigations of the interplay of methods and characteristics of user-generated datasets as well as respective methodological innovations form one core key focus of the lab. Methodologically, the lab is thereby specialised in approaches to spatial autocorrelation but also covers topics like spatial heterogeneity, hot-spots, and spatial regression.
User-generated datasets do not require the addressing of specific characteristics but may call for a more fundamental paradigmatic shift in how we disclose spatial pattern. For instance, when investigating social media data, we are not dealing with objective information but subjective expressions reflecting feelings, perception, ones’ biography and prior experiences, among many further aspects of how people experience and conceptualise the world. Patterns disclosed by traditional methods from the spatial domain and found in abstract (often geometric) space may thus not be meaningful. Instead, what we need to find is a suitable notion of pattern detection in what human geographers refer to as “place space”. Since place research has been predominately qualitative, pattern detection and statistical analysis of partly subjective places is a novel field that has not yet been fully conceived. Contributing to this highly innovative field is the second pillar of the Spatial Modelling Lab in Dortmund.

Candidate Profile:

The ideal candidate is computationally and geographically educated. You have research interests strongly aligned with the foci of the lab as outlined in the respective section and are acquainted with concepts from human geography, quantitative statistical analysis, and/or geoinformatics. You conducted your PhD research in either Geography, Geoinformatics, Statistics, the Social Sciences, Psychology, Computer Science, or any cognate field. Beyond these requirements, you are open to an interdisciplinary research environment with an international focus. Your attitude is a welcoming and collaborative one. You are seasoned in publishing in international journals and at top notch conferences.

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