Forschungszentrum Julich, Germany invites online Application for number of Fully Funded PhD Positions at various Departments. We are providing a list of Fully Funded PhD Programs available at Forschungszentrum Julich, Germany.
Eligible candidate may Apply as soon as possible.
(01) PhD Positions – Fully Funded
PhD position summary/title: PhD position – Predicting the stress field in atherosclerotic plaque of arteries using scientific machine learning within the HDS-LEE graduate school
We are looking for a PhD student to develop learning-based surrogate models for predicting stress fields in patient-specific arteries. Especially high stresses in plaque can lead to rupture, which is one cause of a stroke and thus the prediction of plaque rupture is very relevant. The steps in the development of surrogate models are building data-driven models from medical imaging, extending them with physics-based approaches, and adapting existing physics-integrated neural network approaches for stress prediction in arterial walls and plaque. Another part of the project is exploring the use of large language models to support neural network design and data preprocessing. The position involves close collaboration with experts in cardiovascular simulation and Scientific Machine Learning.
Your tasks:
- Development and comparison of data driven models for the prediction of stresses in arterial walls and plaque
- Enhancing the models with physics, i.e., using different physics-aware machine learning models from the field of scientific machine learning
- Exploiting large language models to support neural network design and data preprocessing
- Participation in conferences in Germany and abroad (incl. presenting your research results)
- Preparing scientific publications and project reports
Deadline : Open until filled
(02) PhD Positions- Fully Funded
PhD position summary/title: PhD position – GPU-accelerated parallel training of physics-aware neural networks for blood flow prediction within the HDS-LEE graduate school
We are looking for a PhD student to contribute to the development of fast, accurate, and physics-informed machine learning models for predicting blood flow in patient-specific vascular geometries. Current simulation-based approaches require complex 3D meshes and are often too slow for practical medical use. This project aims to create accurate and rapid surrogate models by combining physics-aware learning methods with domain decomposition techniques, enabling parallel training and efficient GPU-supported implementation.
Your tasks:
- Development of physics-aware ML models for 3D blood-flow prediction
- Integration of domain decomposition methods into the learning framework to enable efficient model parallel training
- Implementation and optimization of GPU-accelerated training pipelines
- Validation of models on patient-specific geometries obtained from MRI data
- Participation in conferences in Germany and abroad (incl. presenting your research results)
- Preparing scientific publications and project reports
Deadline : Open until filled
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(03) PhD Positions – Fully Funded
PhD position summary/title: PhD Position – Process and plant engineering for chemical hydrogen storage
Deadline : Open until filled
(04) PhD Positions – Fully Funded
PhD position summary/title: PhD Position – Experimental characterization of supercritical steam reforming of methanol and dimethyl ether
- Coordination, commissioning and trial operation of a high-pressure reactor for the steam reforming of methanol and dimethyl ether
- Experimental characterization of steam reforming under supercritical reaction conditions
- Working with commercial and academic catalysts
- Kinetic investigation & modelling of supercritical steam reforming
- Integration of experimental results into reactor and process simulation
- Analysis and presentation of results at scientific conferences and in journals
- Support in the preparation of third-party funding applications
- Participation in academic teaching and public relations work
Deadline : Open until filled
(05) PhD Positions – Fully Funded
PhD position summary/title: PhD Position – Earth System Science within the HDS-LEE graduate school
The PhD position is offered in the context of the HDS-LEE graduate school. We are looking for a highly motivated PhD candidate to join our world-leading research program in Earth System modelling and improving Earth System Modeling by better merging of measurement data and model simulations.
This PhD project focuses on improving how we estimate key parameters in land-surface and ecosystem models, which are essential for understanding climate change impacts. The work involves reviewing existing modeling and model–data fusion techniques, and developing faster, machine-learning–based tools that can stand in for slow model simulations. These tools will be used to test how model parameters influence results and to make parameter estimation more efficient. The project will apply and evaluate these new methods at different sites and time periods, compare them with established approaches, and finally demonstrate their potential in a Europe-wide ecosystem reanalysis.
Deadline : Open until filled
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(06) PhD Positions- Fully Funded
PhD position summary/title: Several PhD positions – Simulation and Data Lab Digital Bioeconomy (four positions)
You will work as a doctoral researcher within one of four interdisciplinary PhD projects in the Simulation and Data Lab Digital Bioeconomy. Each project combines natural sciences with computational and data-driven approaches, focusing on topics such as plant carbon transport, microbial systems, or circular bioprocesses. You will contribute to developing and applying novel modeling strategies, AI-enhanced simulations, and computational workflows to explore biological complexity and design solutions for a sustainable bioeconomy.
Deadline : Open until filled
(07) PhD Positions – Fully Funded
PhD position summary/title: PhD position – Bridging classical and AI-based approaches for the analysis of massively parallel neural spike trains within the HDS-LEE graduate school
This PhD project bridges between classical analytical methods and modern AI based techniques to analyse spike train recordings to advance our understanding of neural population coding while maintaining clarity in the interpretation of results. Concurrently, AI-based methods are developed that prioritize interpretability and reduce data dependency by imposing desirable constraints on model behavior.
Deadline : Open until filled
(08) PhD Positions – Fully Funded
PhD position summary/title: PhD position – Linking rate manifolds to higher-order spike patterns across cortical layers and brain regions within the HDS-LEE graduate school
This PhD project aims at relating precisely timed spike constellations across subsets of neurons to low-dimensional manifolds of high-dimensional space of population neuronal firing rates. Thus neuronal experimental data are to be analyzed for both aspects by PCA analysis and statistical multivariate methods to extract spatio-temporal spike patterns. Finally both results will be linked and related in space and time and to behavioral events.
Deadline : Open until filled
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(09) PhD Positions – Fully Funded
PhD position summary/title: PhD Position – Quantitative evaluation of (macro)economic impacts related to energy system transformations
- Maintain, and update quantitative methods for assessing economic impacts of the energy transition at the national and regional levels
- Develop dynamic and multisectoral economic models to gain insights into complex systems and inform decision-making
- Design and evaluate scenarios that focus on energy systems and structural change, assessing their potential impact
- Develop and evaluate transformation paths that are necessary to address the challenges posed by climate change
- Present research findings at national and international conferences, utilizing effective communication skills to convey insights clearly and succinctly
- Publish research results in reputable scientific journals to share knowledge and contribute to the advancement of the field
Deadline : Open until filled
(10) PhD Positions – Fully Funded
PhD position summary/title: PhD Position – Interactive Learning for Closed-Loop Control of Microfluidic Live-Cell Experiments (HDS-LEE graduate school)
We are looking for a PhD student in machine learning to work within a project linked to the “Helmholtz School for Data Science in Life, Earth and Energy (HDS-LEE)”.
Your Job:
- Develop physics-aware simulations of growing cell populations, including their spatiotemporal manipulation in microfluidic environments
- Design and implement reinforcement learning algorithms for control and manipulation, first in simulation and later on real experimental setups
- Refine a real-time planning and execution architecture for information-driven experiment steering (closed-loop control)
- Work in an interdisciplinary team of engineers, computer scientists, and life scientists
- Present your work at international conferences and learn about state-of-the-art methods in machine learning, reinforcement learning and computer vision for the life sciences
Deadline : Open until filled
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(11) PhD Positions – Fully Funded
PhD position summary/title: PhD Position – High-Fidelity Multi-Instance Modeling of Living Symbioses: 3D+t Reconstruction of Paramecia and Symbionts from Live-Cell Microscopy (HDS-LEE graduate school)
We are looking for a PhD student in machine learning to work within a project linked to the “Helmholtz School for Data Science in Life, Earth and Energy (HDS-LEE)”.
Your Job:
- Develop 3D+t image reconstruction methods in a cell microscopy setting using image sequences as well as focus stacks
- Investigate instance and panoptic segmentation for endosymbionts and track them over time
- Implement, train and test novel machine-learning-based solutions on top-tier super-computing hardware
- Work in an interdisciplinary team of engineers, computer scientists, and life scientists
- Regularly participate in international conferences to present your own work, and learn about state-of-the-art machine learning and computer vision methods and their applications
Deadline : Open until filled
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(12) PhD Positions – Fully Funded
PhD position summary/title: PhD position – Co-regulation structures for large-scale single-cell transcriptomics – within the HDS-LEE graduate school
Deadline : Open until filled
(13) PhD Positions – Fully Funded
PhD position summary/title: PhD position – Probabilistic Metabolic Flux Analysis within the HDS-LEE graduate school
This PhD project develops a Bayesian inference framework for hybrid model- and data-driven modeling of metabolism, with a particular focus on handling model misspecification. By combining Bayesian computational statistics, differentiable programming, and high-performance computing, the project aims to deliver robust, interpretable, and scalable methods for metabolic flux analysis.
Deadline : Open until filled
(14) PhD Positions – Fully Funded
PhD position summary/title: PhD position – Learning Tailored Iterative Algorithms for Accelerating AC Power Flow Computations (HDS-LEE graduate school)
Energy systems engineering heavily relies on efficient numerical algorithms. In this HDS-LEE project, we will use machine learning (ML) along with data from previously solved problem instances to solve new, yet similar, instances more efficiently than with general purpose algorithms such as Netwon`s method. In particular, we aim to develop a neural network architecture that will allow us to accelerate solving AC power flow (AC-PF) computations, potentially facilitating real‑time contingency analysis, rapid design‑space exploration, and on‑line operational optimization of power systems.
Deadline : Open until filled
(15) PhD Positions – Fully Funded
PhD position summary/title: PhD position – Machine learning based assimilation of satellite data to improve air quality predictions (HDS-LEE graduate school)
Remote sensing data from satellites are an extremely valuable information source to improve air quality predictions. They monitor aerosol and trace gases often with global coverage, which is far beyond in-situ observational networks. However, the accuracy of satellite retrievals depends on several assumptions leading to biased observations.
- The aim of the PhD-project is to overcome this limitation in the use of satellite observations by make a direct use of radiance observations retrieved by satellites using machine learning without the need of radiative transfer calculations. The new model will be developed using the example of the novel Earth Explorer EarthCARE and will be integrated as observation operator to the sophisticated data assimilation system of the EURopean Air pollution Dispersion – Inverse Model (EURAD-IM).
Deadline : Open until filled
(16) PhD Positions – Fully Funded
PhD position summary/title: PhD position – Understanding the Transport of Aerosol Particles in the Upper Troposphere and Lower Stratosphere and Their Interaction with Ice Clouds
Aerosol particles act as ice nucleating particles, providing surface for water vapour to deposit and freeze into ice particles. Formation of cirrus clouds and subsequent sedimentation of ice crystals can dehydrate air in the upper troposphere and lower stratosphere (UTLS) region, thereby influencing the water vapor budget of this region. Aerosols and cirrus are important to the global climate because they interact with radiation from the sun and from the earth. However, the aerosol-cirrus interaction in the UTLS is not well understood because of lacking sufficient in situ data. In addition, the dynamics and transport processes across the UTLS adds complexity to unveil the role of UTLS aerosols in cirrus formation and the life cycle of cirrus. Therefore, it is crucial to measure aerosol composition and properties together with cirrus occurrences in the UTLS for achieving a better understanding of the link between aerosols and cirrus clouds in the UTLS, for which Lagrangian modelling is a valuable tool to revealing the source of UTLS aerosols, the origin of water masses, and formation processes of cirrus particles.
Deadline : Open until filled
(17) PhD Positions – Fully Funded
PhD position summary/title: PhD Position – Development and implementation of methods to visualize and quantify radiation damage
The aim of the project is to commission new testing facilities for determining mechanical, thermophysical and microscopic material properties inside and outside the hot cells and to further develop standardised methods for examining irradiated samples after irradiation to quantify radiation damage.
- Supervision of the manufacture and assembly of equipment inside and outside hot cells for the examination of irradiated samples
- Production and metallography of samples for electron microscopy
- Development and implementation of methods for visualising and quantifying radiation damage using transmission electron microscopy
- Differentiation and quantification of displacement and transmutation damage in irradiated samples using electron microscopy and glow discharge optical emission spectroscopy
- Presentation of research results at national and international conferences and publication in renowned journals.
- Collaboration with internal and external project partners at the research centre and at national and international research sites
Deadline : Open until filled
(18) PhD Positions – Fully Funded
PhD position summary/title: PhD Position – Agroecosystem Digital Twins and Drone-Based Data Assimilation
The PhD position is offered within the Cluster of Excellence PhenoRob – Robotics and Phenotyping for Sustainable Crop Production. We are looking for a highly motivated PhD candidate to join our world-leading research program in robotics, remote sensing, and data-driven approaches for sustainable agriculture. PhenoRob’s mission is to transform crop production by optimizing breeding and farm management through innovative sensing technologies, advanced modeling, and intelligent automation.
This PhD project contributes to PhenoRob’s initiative to develop digital twins, i.e., high-fidelity virtual representations of agricultural ecosystems. These digital twins will enhance our understanding of ecosystem functioning and carbon fluxes, supporting the design of more sustainable and resilient crop production systems. The project will focus on integrating high-resolution drone-based remote sensing data, including multispectral and thermal imagery as well as LiDAR measurements, into ensemble agroecosystem model simulations. The successful candidate will play a key role in developing robust landscape-scale digital twins and advancing data assimilation techniques for agricultural and environmental applications.
Deadline : Open until filled
(19) PhD Positions- Fully Funded
PhD position summary/title: PhD Position – Development of efficient electro-catalysts for the electrochemical conversion of liquid organic hydrogen carriers
The electrocatalytic interface engineering department, led by Prof. Dr.-Ing. Simon Thiele focuses on the manufacturing, analysis, and simulation of functional materials to find an optimal structure on small scales, ranging from the micrometer to the nanometer scale. The investigated materials and systems play a crucial role in sustainable technologies, such as water- and CO2-electrolyzers, as well as fuel cells. Your main responsibilities include:
- Synthesis and characterization of catalyst particles for electrochemical hydrogenation and dehydrogenation of liquid organic hydrogen carrier (LOHC) in electrochemical ion exchange membrane reactors.
- Manufacturing of catalyst layers using the novel synthesized catalysts by using spray coating or doctor blade-coating technique for application in electrochemical ion exchange membrane reactors like fuel cells or electrolysers
- Physical, spectroscopic, and electrochemical characterization of membrane electrode assemblies prior to, during, and after cell operation
- Participation in project meetings
- Coordination with internal and external project partners
- Publication and presentation of research results in relevant journals or at international conferences
Deadline : Open until filled
(20) PhD Positions – Fully Funded
PhD position summary/title: PhD Position – Advancing Root Phenotyping and Soil Function Exploration Through Non-Invasive Agrogeophysics
The PhD project offered will be part of the Cluster of Excellence: PhenoRob – Robotics and Phenotyping for Sustainable Crop Production. PhenoRob performs world-leading research in robotics and phenotyping for sustainable crop production with the vision to transform crop production by optimizing breeding and farming management through developing and deploying new technologies. Within Phenorob, we develop novel agrogeophysical methods to obtain noninvasive subsoil information that can be used to advance root phenotyping and soil functions. Soil-root interactions will be analyzed across management scenarios using geophysics and numerical modeling. High-resolution subsoil characterization using electromagnetic induction (EMI), and ground penetrating radar (GPR) will be combined with soil sensors systems and UAVs at different scales. In particular, we will combine borehole and surface GPR as well as small-scale EMI measurements with root and shoot observations in controlled experiments (rhizotron facility) and field trials. In addition to field applications, novel inversion algorithms for ground-penetrating radar (GPR) and electromagnetic (EM) will be developed. These algorithms will enable high-resolution, quantitative time-lapse soil property measurements using high-performance, parallel computing. Together with our existing rich dataset, we will inform a soil-plant digital twin, enabling ML-based analysis of geophysical and rover approaches for field-scale root and soil characterization.
Deadline : Open until filled
(21) PhD Positions – Fully Funded
PhD position summary/title: PhD Position – Spatial structural analyses of crowds
In the CrowdING project, you will analyze experimental data from large crowds and develop quantitative measures to describe their spatial structure. To do this, you will use and expand methods such as Minkowski functionals, Voronoi-based density analyses, and modern cluster and pattern recognition techniques. Your goal is to precisely capture the structural characteristics of crowds and investigate how they change under different conditions. The analyses are always carried out in conjunction with social-psychological findings on the perception of crowds, thus contributing to an integrated understanding of physical and social morphology. The work is carried out in close collaboration with project partners at the University of Wuppertal and the University of Groningen (NL). Your tasks will include:
- Quantitative analysis of experimental data and description of spatial structures in crowds (e.g., Minkowski functionals, Voronoi analyses, clustering methods)
- Comparison of physical structural analyses with social psychological findings
- Integration and further development of measurement methods and measurements in the PedPy library
- Collaboration in the planning, implementation, and evaluation of crowd experiments
- Exchange and close cooperation with partners from physics, computer science, and social psychology
- Publication of research results in international journals
- Presentations at international conferences and participation in project workshops in Wuppertal and Groningen (NL)
Deadline : Open until filled
(22) PhD Positions – Fully Funded
PhD position summary/title: PhD Position – Agent-based models for crowd dynamics
In the CrowdING project, you will develop agent-based movement models that realistically simulate different behaviors such as lining up, overtaking, or pushing. Based on this, you will analyze how these behavioral differences affect collective phenomena in large crowds. The models will be integrated into the JuPedSim simulation environment and further developed there. To support model development and validation, you will also participate in the planning and execution of laboratory experiments and the analysis of the collected data. The project is being carried out in close collaboration with the University of Wuppertal and the University of Groningen (NL). Your tasks will include:
- Developing agent-based movement models with different movement strategies
- Analyzing how these different movement strategies influence collective phenomena in crowds
- Integrating and further developing the models in the JuPedSim simulation framework
- Evaluating experimental data to validate and improve the models
- Exchanging ideas and working closely with partners from physics, computer science, and social psychology
- Collaboration in the planning, implementation, and evaluation of crowd experiments
- Publication of research results in international journals
- Presentations at international conferences and participation in project workshops in Wuppertal and Groningen (NL)
Deadline : Open until filled
(23) PhD Positions – Fully Funded
PhD position summary/title: PhD Position – Co-Optimization and Prototyping of Biophysics-Inspired Algorithms and Circuits
This research primarily seeks to incorporate advanced neuron models, such as those capturing dendritic computation and probabilistic Bayesian network behavior, into unconventional computing architectures, replacing conventional structureless and deterministic LIF point-neuron models. This is pursued through circuit designs that exploit and control memristor dynamics (e.g., local activity and stochasticity). For example, localized dendritic activation underlies numerous computational functions across hierarchical levels, such as denoising (filtering), increased expressivity (tunable local activation), multi-timescale adaptation (local memory), and stimulus-specific adaptation (multi-task processing). While the co-optimization of dendrite-inspired functional circuits with emerging memory devices has only recently been explored, this doctoral project aims to advance that frontier.
Initially, the research will explore CMOS–memristor hybrid implementations, leveraging their analog tunability and high-order dynamics to realize dendrite-inspired functional circuits. These circuits will subsequently be integrated as core computational modules within unconventional computing architectures, enabling algorithm–circuit co-optimization across the computing pipeline with respect to key metrics such as power consumption, computational delay, and area efficiency. Beyond circuit prototyping, the project will conduct task-level benchmarking to evaluate overall system performance in relation to both dendrite–neurosynaptic functionalities and the intrinsic characteristics of memristive devices.
Deadline : Open until filled
(24) PhD Positions – Fully Funded
PhD position summary/title: PhD position – Stability of Inverter-Based Power Systems
Deadline : Open until filled
(25) PhD Positions – Fully Funded
PhD position summary/title: PhD Position – Ensuring Power System Security under Extreme Conditions using Exascale Computing
In this PhD project, you will shape the future of power system security by harnessing exascale computing. Your research will focus on understanding and enhancing grid resilience under extreme scenarios.
Deadline : Open until filled
(26) PhD Positions – Fully Funded
PhD position summary/title: PhD position – Analysis of Transformation Pathways for European Gas and Hydrogen Grids in Integrated Energy Systems
- Investigate the impacts of future transformation pathways on the operational security and resilience of gas and hydrogen infrastructures, considering hydrogen blending, pipeline repurposing, and Power-to-Gas technologies
- Evaluate and compare system operational behaviours under diverse policy and market scenarios (e.g., hydrogen import strategies, regional demand developments) through scenario-based modelling
- Assess the interactions between gas, electricity, and heat sectors, focusing on operational flexibility, cross-sectoral dependencies, and potential bottlenecks
- Enhance and extend our simulation tools and models (GasNetSim) to meet evolving research requirements and support comprehensive system analyses
- Extend our simulation tool (GasNetSim) and grid models to fulfil research needs
- Disseminate your findings through scientific publications, conferences, and collaborations
- Supervise Bachelor’s and Master’s students and represent the institute in national and international research contexts
Deadline : Open until filled
(27) PhD Positions – Fully Funded
PhD position summary/title: PhD Position – Filming nanocatalysts for renewable energies
At the Electrocatalysis department of Prof. Karl Mayrhofer, we offer a PhD position within the team Nanoanalysis of Electrochemical Processes. Lead by Dr. Andreas Hutzler, the team is investigating degradation mechanisms within the framework of green energy conversion and climate change. The open position aims to understand catalyst stability at the nanoscale during electrochemical processes via operando liquid-phase transmission electron microscopy (LP-TEM). Your tasks:
- Self-motivated and independent planning, execution, and analysis of research in the scope of operando electrocatalysis using LP-TEM
- Execution of TEM analyses as part of our TEM facility at HI ERN
- Presentation of scientific results at national and international conferences as well as publication in peer-reviewed journals
Deadline : Open until filled
(28) PhD Positions – Fully Funded
PhD position summary/title: PhD Position – Degradation of electrodes in water electrolysis
You will be part of the Electrochemical Energy Conversion group of the Electrocatalysis research unit of the HI ERN. In fundamental and applied research, we focus on understanding the complex interplays between materials` properties and the electrochemical environment and their influences on materials` electrochemical performance. By developing and implementing new experimental tools in electrocatalysis research, we aim to significantly contribute to the development of electrochemical energy conversion as a future key player for electromobility and the energy policy in general.
Your tasks primarily focus on the following topics:
- Development and application of experimental platforms for studying electrocatalysts and real electrodes for water electrolysis applications
- Integration of mass spectrometry techniques to study degradation processes, including electrocatalyst dissolution
- Mechanistic understanding of catalyst degradation processes in PEM, AEM, and alkaline water electrolysis
- Implementation of AI-based tools in water electrolysis research
- Collaboration with computer science, catalyst synthesis and characterization, and theory groups to optimize water electrolysis using the knowledge obtained in the project
Deadline : Open until filled
(29) PhD Positions – Fully Funded
PhD position summary/title: PhD-Position – Quantitative modelling of Sperm Dynamics
This work will be performed as part of an agile team unified by a common goal: An Industry partner from semen production provides fresh sperm cells and pre-analysis. A second industry partner from data sciences provides data management and AI based Image analysis, an internal experimental group, and an internal simulation-sciences group (You+Supervisor+support by lab). These collaborations enable practically relevant and breakthrough results.
This team goal requires a quantitative model describing and predicting sperm motility under various conditions. You will develop the digital twin of sperm motility, and utilize it to develop a separation method. Your tasks will include:
- Performing computer simulations and matching them to experimental data
- Very close collaboration with experiments, including occasional wet lab work
- Merging experimental results, simulations, and literature for optimal conditions inducing movement differences, in collaboration with the team.
- Participation in conferences in Germany and abroad (incl. presenting your research results)
- Travel to industry partners to learn and set up on-site research
- Preparing scientific publications and project reports
Deadline : Open until filled
(30) PhD Positions – Fully Funded
PhD position summary/title: PhD Position – Quantifying Sperm Dynamics
This work will be performed as part of an agile team unified by a common goal: An Industry partner from semen production provides fresh sperm cells and pre-analysis. A second industry partner from data sciences provides data management and AI based Image analysis, an internal simulations group working on quantitative models to reproduce and predict experimental data, and an internal experiments group (You+Supervisor+support by lab). These collaborations enable practically relevant and breakthrough results.
This team goal requires initially videomicroscopy of X-Y fluorescently labeled sperm cells to develop a quantitative model. Once established, predicted separation mechanisms need to be tested. You will perform these experiments.
Your tasks will include:
- Adapt existing DNA labeling protocols to our Workflow
- Performing microscopy experiments on sperm dynamics under various controlled environmental conditions.
- Merging experimental results, simulations, and literature for optimal conditions inducing movement differences, in collaboration with the team.
- Testing proposed separation techniques
- Participation in conferences in Germany and abroad (incl. presenting your research results)
- Travel to industry partners to learn and set up on-site research
- Preparing scientific publications and project reports
Deadline : Open until filled
(31) PhD Positions – Fully Funded
PhD position summary/title: PhD Position – Quantum photonics in curved spacetime
Deadline : Open until filled
(32) PhD Positions – Fully Funded
PhD position summary/title: PhD-Position – Development of scalable superconducting quantum systems
This position focuses on building, operating, and testing superconducting quantum devices. Your tasks in detail are:
- Design and fabrication of superconducting quantum circuits
- Setting up experimental systems for cryogenic measurements
- Development of a microwave quantum control & readout stack
- Development of Python code to operate quantum systems
- Detailed experimental characterization of superconducting qubits to quantify performance and identify limiting physical mechanisms
- Perform quantum device calibrations, benchmarking, and run quantum algorithms
- Presenting and publishing the research on an international stage
Deadline : Open until filled
(33) PhD Positions – Fully Funded
PhD position summary/title: PhD position in optical instrumentation for NASA’s AtmoCube mission
- Conduct the assembly, verification, and calibration of a novel optical instrument in our Cleanroom-5 laboratory at the University of Wuppertal
- Work with a variety of calibration units, optimize and extend existing setups, develop a novel setup to perform an absolute radiometric calibration
- Perform a line-of-sight calibration to precisely align the instrument’s viewing geometry with the satellite’s star cameras
- Support the integration of the optical payload into the satellite at our partner site in Boulder, Colorado
- Participate in in-orbit calibration activities during the Commissioning and Early Operations phases
- Present your research at international conferences and in peer-reviewed journals
Deadline : Open until filled
(34) PhD Positions – Fully Funded
PhD position summary/title: PhD Position – Organic Electrosynthesis: monitoring of reaction transients with real-time techniques
The Electrocatalysis research department (https://www.hi-ern.de/hi-ern/Electrocatalysis) is looking for three PhD students, which research area is to investigate fundamental relationships between electrolyte-electrode interface structure and selectivity or efficiency of chemical outcome during the preparation of complex and value-added compounds directly from the readily available feedstock. Organic synthesis under electrochemical conditions is a powerful tool for future sustainable chemical manufacturing, for which robust catalytic materials are of high demand. A unique platform for online real-time analysis of electrochemical processes, developed in the Department of Electrocatalysis, will be applied by You to discover and develop novel Organic Electrosynthetic Protocols. Your tasks for selected electro-organic transformation in detail:
- Design, validation and verification of online and offline analytical methods
- Design, synthesis, and characterization of catalytic materials
- Utilization of the obtained materials as electrocatalysts
- Analysis of the activity, selectivity, and stability of electrocatalysts
- Communication of the experimental data obtained
- Writing papers and presenting the results at conferences
- Representing the institute in project meetings and collaboration with partners within HI ERN and outside
Deadline : Open until filled
(35) PhD Positions – Fully Funded
PhD position summary/title: PhD Position – Design and development of an in-house X-ray beamline for long term operando investigation of chemical hydrogen storage reactors
Deadline : Open until filled
(36) PhD Positions – Fully Funded
PhD position summary/title: PhD Student – Investigation of the continuous butanediol dehydrogenation under dynamic hydrogen release using pressure control
As part of your activities, you will carry out investigations of the continuous butanediol dehydrogenation under dynamic hydrogen release using pressure control in the laboratories on the campus of Forschungszentrum Jülich. Your tasks include in detail:
- Construction and commissioning of a new test stand for the investigation of the continuous butanediol dehydrogenation under dynamic hydrogen release by means of pressure control
- Carrying out parameter studies
- Comparison of different catalyst materials
- Determination of the pressure dependence of the dynamic hydrogen release
- Development and validation of various test stand modifications
- Coordination with internal and external project partners from industry and research
- Publication and presentation of research results in relevant journals and at national and international conferences
- Participation in the development of the institute
Deadline : Open until filled
(37) PhD Positions – Fully Funded
PhD position summary/title: PhD Student – Regeneration of coked catalysts form LOHC dehydrogenation
As part of your doctoral project, you will focus on the development of strategies for the regeneration of catalysts that deactivate in the release of hydrogen from the liquid organic hydrogen carrier (LOHC) perhydrobenzyltoluene. Your task will include:
- Planning and commissioning of a test rig for the dyhydrogenation of loaded LOHC
- Targeted deactivation of the catalyst materials under harsh process conditions
- Investigation of the underlying deactivation mechanisms
- Development of regeneration strategies for deactivated catalysts
- Coordination with internal and external project partners from industry and research
- Publication and presentation of research results in relevant journals and at national and international conferences
- Collaboration with other working groups at Forschungszentrum Jülich
- Participation in the development of the institute
Deadline : Open until filled
(38) PhD Positions – Fully Funded
PhD position summary/title: PhD Position – Characterization of new catalyst layer structures and electrolytes for anion exchange membrane water electrolysis
The electrocatalytic interface engineering department led by Prof. Dr.-Ing. Simon Thiele focuses on synthesis, manufacturing, analysis and simulation of functional materials to find an optimum structure on small scales from the micrometer to the nanometer scale. The investigated materials and systems play an essential role in sustainable technologies like water- and CO2-electrolyzers, as well as in fuel cells. Some of your responsibilities will include:
- Design and set-up of new testing equipment and procedures for application-driven characterization of new materials for water electrolysis
- Manufacturing of catalyst layers and membrane electrode assemblies (MEAs) for electrochemical characterization
- Physical, spectroscopic, and electrochemical characterization of MEAs prior to, during, and after operation
- Participation in project meetings.
- Coordination with internal and external partners
- Publication and presentation of research results in relevant journals and at international conferences
Deadline : Open until filled
About Forschungszentrum Julich, Germany –Official Website
Forschungszentrum Jülich is a member of the Helmholtz Association of German Research Centres and is one of the largest interdisciplinary research centres in Europe. It was founded on 11 December 1956 by the state of North Rhine-Westphalia as a registered association, before it became “Kernforschungsanlage Jülich GmbH” or Nuclear Research Centre Jülich in 1967. In 1990, the name of the association was changed to “Forschungszentrum Jülich GmbH”. It has close collaborations with RWTH Aachen in the form of Jülich-Aachen Research Alliance (JARA).
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