field_remote_option

field_job_employment_type

job_industry

field_job_occupational_field_parents_all

job_organization_name

<h2>Weitere Informationen</h2><p>The successful candidate will be employed under a regular employment contract.<br>The position is to be filled at the earliest possible date and offered for a fixed term of three years.<br>The fixed-term employment is possible as it constitutes one of the fixed-term options of the Wissenschaftszeitvertragsgesetz (German Act on Fixed-term Scientific Contracts).<br>This is a part-time position (75 % of the standard weekly hours for full-time employees).<br>The successful candidate has the opportunity to pursue a doctoral degree in this position.<br>The salary is based on the German public service salary scale (TV-L).<br>The position corresponds to a pay grade of EG 13 TV-L.</p><h2>Unser Profil</h2><p>The Chair of Engineering Geology at RWTH Aachen University has around 35 employees conducting research in the fields of rock mechanics, geomechanics and natural hazards. In addition to the basic equipment, the chair is financed by numerous national and international third-party funded projects. The Chair is involved in the degree courses in Applied Geosciences and Georesource Management.</p>
<p>We are a group of dynamic and internatonal scientists with interests in all aspects of experimental and computational rock mecahnics, with a strong focus on applied topics.</p>
<p><strong>Project title:</strong> Impact of Stress Corrosion and Long-Term Strength of Crystalline Rocks on Barrier Integrity – From Micro-to-Macro Scale (ACCELERATE)</p>
<p><strong>Project description:</strong> Development of brittle damage around tunnels is quite common in massive rocks under highly-stressed conditions. Understanding the shape and extent of the Excavation Damage Zone (EDZ), and its development over time is of foremost relevance for safety analysis of deep geological repositories for nuclear waste. Within the EDZ, permeability is often increased and contains preferred and interconnected flow pathways for the migration of radionuclides. Processes of long-term crack development in crystalline rocks are often associated with stress corrosion and sub-critical crack growth in chemically reactive environments. This is particularly relevant for radioactive waste repositories with elevated rock temperatures. At present, extensive research is being carried out to assess the suitability of various host rock formations—such as rock salt, clay rock, and crystalline rock—that are being considered in Germany for deep geological nuclear waste disposal. Within the ACCELERATE project, we aim to advance our understanding of the long-term behaviour of crystalline rocks through a combination of experimental, in-situ, and numerical approaches.&nbsp;</p><h2>Ihr Profil</h2><p><strong>Candidate Requirements</strong>:</p>
<ul>
<li>Master degree (or comparable) in a project-related discipline (e.g. applied geosciences, engineering geology, geotechnical engineering, geology, geophysics)</li>
<li>Preferably sound knowledge of rock mechanics, petrophysical and micro-structural analysis</li>
<li>Willing to carry out frequent fieldworks in the tunnel</li>
<li>Reliable, ambitious, and able to work both independently and with a team</li>
<li>Excellent written and oral communication skills in English, knowledge of German is considered an asset.</li>
<li>Ability to quickly develop related research skills and knowledge</li>
<li>In procession of a valid driving license (or be able to obtain one) for driving in European Union</li>
</ul><h2>Ihre Aufgaben</h2><p><strong>We are looking for a PhD candidate for the following tasks:</strong></p>
<ul>
<li>Sample selections and performing a series of mineralogical, geochemical and petrophysical tests</li>
<li>Planning, execution and interpretation of rock mechanics and fracture mechanics laboratory testing including short-term and long-term mechanical testing</li>
<li>Micro-structural analysis using optical and electron microscopy</li>
<li>Carrying out frequent fieldworks at the Bedretto Tunnel (Switzerland) to collect in-situ data</li>
<li>Analysis and interpretation of the multi-disciplinary data obtained from various monitoring sources (strain and permeability measurements, seismic data) to understand the evolution of the EDZ both spatially and temporally at PRECODE Tunnel</li>
<li>Coordination with other project partners</li>
</ul><h2>Über uns</h2><p>RWTH is a certified family-friendly University. We support our employees in maintaining a good work-life balance with a wide range of health, advising, and prevention services, for example university sports. Employees who are covered by collective bargaining agreements and civil servants have access to an extensive range of further training courses and the opportunity to purchase a job ticket. <br>RWTH is an equal opportunities employer. We therefore welcome and encourage applications from all suitably qualified candidates, particularly from groups that are underrepresented at the University. All qualified applicants will receive consideration for employment and will not be discriminated against on the basis of national or ethnic origin, sex, sexual orientation, gender identity, religion, disability or age. RWTH is strongly committed to encouraging women in their careers. Female applicants are given preference if they are equally suitable, competent, and professionally qualified, unless a fellow candidate is favored for a specific reason.<br>As RWTH is committed to equality of opportunity, we ask you not to include a photo in your application.<br>You can find information on the personal data we collect from applicants in accordance with Articles 13 and 14 of the European Union's General Data Protection Regulation (GDPR) at <a href="http://www.rwth-aachen.de/dsgvo-information-bewerbung" target="_blank">http://www.rwth-aachen.de/dsgvo-information-bewerbung</a>.</p><h2>Besoldung / Entgelt</h2><p>EG 13 TV-L</p>

Land Nordrhein-Westfalen

Research Assistant/Associate (f/m/d) PhD Position in Engineering Geology Geoscientist, geotechnical engineer or similar

<h2>Weitere Informationen</h2><p>The successful candidate will be employed under a regular employment contract.<br>The position is to be filled at the earliest possible date and offered for a fixed term initially to three years.<br>The fixed-term employment is possible as it constitutes one of the fixed-term options of the Wissenschaftszeitvertragsgesetz (German Act on Fixed-term Scientific Contracts).<br>This is a full-time position.<br>The successful candidate has the opportunity to pursue a doctoral degree in this position.<br>The salary is based on the German public service salary scale (TV-L).<br>The position corresponds to a pay grade of EG 13 TV-L.</p><h2>Unser Profil</h2><p>The Chair of Imaging and Computer Vision (LFB) conducts pioneering research at the intersection of imaging instrumentation and computational imaging, ranging from the development of novel hybrid imaging systems to advanced image reconstruction and video communication. Building on this broad interdisciplinary expertise, we specifically focus on robust 3D reconstruction of anatomical structures and multimodal image analysis. By combining hybrid machine learning with physical modeling, we develop tailored solutions that bridge the gap between raw imaging data and clinical application, ensuring reliable decision support in complex medical workflows.</p>
<p>Join us at the forefront of medical AI technology as part of a new interdisciplinary research consortium. We are developing a fully automated process chain for surgical planning, specifically addressing dysgnathia and extremity surgery.</p>
<p>You will work in a strong interdisciplinary team alongside our consortium partners, including clinical experts from major university hospitals (providing data &amp; validation), specialized software partners (responsible for platform integration), and experts in manufacturing technology (focusing on production automation).</p>
<p>The project aims to overcome the "data bottleneck" in medical AI. Instead of relying solely on massive manual annotation, we aim to leverage unlabelled data to build intelligent systems that truly "understand" 3D anatomy. We are moving from raw DICOM data to patient-specific, geometry-based surgical guides.</p><h2>Ihr Profil</h2><p>&nbsp;* Education: Master’s degree or comparable in Computer Science, Physics, Engineering, or a related field with a strong focus on AI/ML.</p>
<p>&nbsp;* Technical Skills: Proficient in Python and Deep Learning frameworks (PyTorch). Experience with Self-Supervised Learning (SSL), Transformers, or modern architectures like Masked Autoencoders (MAE) / JEPA is highly desirable.</p>
<p>&nbsp;* Methodological Knowledge: Strong understanding of computer vision, representation learning, and high-dimensional geometry.</p>
<p>&nbsp;* Soft Skills: Passion for solving medical challenges and ability to work in multidisciplinary teams (engineers, clinicians).</p><h2>Ihre Aufgaben</h2><p>You will be responsible for researching and developing next-generation AI methods for 3D medical image understanding, aiming to automate complex surgical planning workflows using modern self-supervised techniques:</p>
<p>&nbsp;* Pioneering Self-Supervised Learning: Investigate and adapt modern Joint Embedding Predictive Architectures (e.g., I-JEPA, V-JEPA) for volumetric medical data (CT/DVT). Your goal is to develop a "Volumetric-JEPA" that learns robust anatomical representations from unlabelled data without relying on pixel-level reconstruction.</p>
<p>&nbsp;* Data-Efficient Segmentation: Utilize these pre-trained semantic backbones to achieve high-precision segmentation of critical structures (e.g., mandible, nerve canals) using Few-Shot Learning. This aims to drastically reduce the need for manual annotations compared to traditional supervised methods.</p>
<p>&nbsp;* Generative vs. Predictive AI: Systematically compare the robustness of predictive architectures (JEPA) against generative approaches (e.g., Diffusion Models, GANs), specifically regarding their ability to handle severe anatomical deformations and image artifacts (OOD robustness).</p>
<p>&nbsp;* Multimodal VLM Interface: Develop interfaces to feed the learned high-level feature embeddings into Multimodal Large Language Models, enabling a semantic "Safety Layer" that validates surgical plans based on anatomical understanding.</p>
<p>&nbsp;* Algorithmic Surgical Planning: Implement geometric algorithms (osteotomy planes, collision analysis) that build upon the robust features extracted by your AI models to automate the planning process.</p><h2>Über uns</h2><p>RWTH is a certified family-friendly University. We support our employees in maintaining a good work-life balance with a wide range of health, advising, and prevention services, for example university sports. Employees who are covered by collective bargaining agreements and civil servants have access to an extensive range of further training courses and the opportunity to purchase a job ticket. <br>RWTH is an equal opportunities employer. We therefore welcome and encourage applications from all suitably qualified candidates, particularly from groups that are underrepresented at the University. All qualified applicants will receive consideration for employment and will not be discriminated against on the basis of national or ethnic origin, sex, sexual orientation, gender identity, religion, disability or age. RWTH is strongly committed to encouraging women in their careers. Female applicants are given preference if they are equally suitable, competent, and professionally qualified, unless a fellow candidate is favored for a specific reason.<br>As RWTH is committed to equality of opportunity, we ask you not to include a photo in your application.<br>You can find information on the personal data we collect from applicants in accordance with Articles 13 and 14 of the European Union's General Data Protection Regulation (GDPR) at <a href="http://www.rwth-aachen.de/dsgvo-information-bewerbung" target="_blank">http://www.rwth-aachen.de/dsgvo-information-bewerbung</a>.</p><h2>Besoldung / Entgelt</h2><p>EG 13 TV-L</p>

Research Assistant/Associate (f/m/d)

<h2>Weitere Informationen</h2><p>The successful candidate will be employed under a regular employment contract.<br>The position is to be filled at the earliest possible date and offered for a fixed term initially to three years.<br>The fixed-term employment is possible as it constitutes one of the fixed-term options of the Wissenschaftszeitvertragsgesetz (German Act on Fixed-term Scientific Contracts).<br>This is a full-time position.<br>The salary is based on the German public service salary scale (TV-L).<br>The position corresponds to a pay grade of EG 13 TV-L.</p><h2>Unser Profil</h2><p>At the Chair of Imaging and Computer Vision, we explore and extend the physical, methodological, and computational limits of modern medical imaging technologies and related domains. Our research spans simulation of novel imaging concepts, hardware prototyping, high-speed data processing, and image reconstruction, complemented by machine and deep learning–based methods for image enhancement, quantitative analysis, and diagnostics. Combining physics-driven and data-driven approaches, we develop next-generation imaging solutions using our in-house systems. Our multidisciplinary team of physicists,engineers, and computer scientists collaborates closely with industry partners and RWTH Aachen spin-offs, ensuring that research outcomes lead to practical impact.&nbsp;</p>
<p>As a Postdoctoral Researcher Fellow, you will join a collaborative team our chair, working closely with Fraunhofer MEVIS to advance the next generation of LF-MRI technology. The research combines system-level innovation - novel gradient, RF and B0 concepts, low-noise acquisition with advanced algorithmic approaches, including AI-driven reconstruction, physics-informed modeling, and adaptive signal processing. Together, these developments aim to redefine the performance limits of LF-MRI and establish it as a powerful, accessible, and scalable imaging modality for the future of healthcare.&nbsp;</p>
<p><strong>Why Join Us:</strong></p>
<ul>
<li>An excellent collaborative, interdisciplinary research environment with leading scientists.</li>
<li>Exciting research opportunities in cutting-edge magnetic imaging technologies.&nbsp;</li>
<li>Access to state-of-the-art low-field MRI and commercial MRI systems.&nbsp;</li>
<li>Opportunity to shape next-generation MRI solutions and contribute to high-impact publications.&nbsp;<br><br></li>
</ul>
<p>&nbsp;</p><h2>Ihr Profil</h2><ul>
<li>Masters`s degree or equivalent and PhD in MRI or a related field with a focus on system innovation.</li>
<li>Solid expertise in B₀/gradient design, RFcoils, data acquisition, and image reconstruction.</li>
<li>Highly independent and self-motivated, with a strong collaborative mindset</li>
<li>Passionate about advancing medical imaging through innovation.</li>
</ul><h2>Ihre Aufgaben</h2><ul>
<li>Develop and optimize hardware components to maximize signal sensitivity.</li>
<li>Investigate multi-channel and resonance-based techniques for improved imaging.</li>
<li>Implement AI-driven signal enhancement strategies.</li>
<li>Collaborate in an interdisciplinary research environment.</li>
</ul><h2>Über uns</h2><p>RWTH is a certified family-friendly University. We support our employees in maintaining a good work-life balance with a wide range of health, advising, and prevention services, for example university sports. Employees who are covered by collective bargaining agreements and civil servants have access to an extensive range of further training courses and the opportunity to purchase a job ticket. <br>RWTH is an equal opportunities employer. We therefore welcome and encourage applications from all suitably qualified candidates, particularly from groups that are underrepresented at the University. All qualified applicants will receive consideration for employment and will not be discriminated against on the basis of national or ethnic origin, sex, sexual orientation, gender identity, religion, disability or age. RWTH is strongly committed to encouraging women in their careers. Female applicants are given preference if they are equally suitable, competent, and professionally qualified, unless a fellow candidate is favored for a specific reason.<br>As RWTH is committed to equality of opportunity, we ask you not to include a photo in your application.<br>You can find information on the personal data we collect from applicants in accordance with Articles 13 and 14 of the European Union's General Data Protection Regulation (GDPR) at <a href="http://www.rwth-aachen.de/dsgvo-information-bewerbung" target="_blank">http://www.rwth-aachen.de/dsgvo-information-bewerbung</a>.</p><h2>Besoldung / Entgelt</h2><p>EG 13 TV-L</p>

Research Assistant/Associate (f/m/d) Postdoctoral Research Fellow in Advanced Low-Field MRI

<h2>Weitere Informationen</h2><p>The successful candidate will be employed under a regular employment contract.<br>The position is to be filled at the earliest possible date and offered for a fixed term of 1 year.<br>An extension for 2 years is provided.<br>The fixed-term employment is possible as it constitutes one of the fixed-term options of the Wissenschaftszeitvertragsgesetz (German Act on Fixed-term Scientific Contracts).<br>This is a full-time position.<br>The successful candidate has the opportunity to pursue a doctoral degree in this position.<br>The salary is based on the German public service salary scale (TV-L).<br>The position corresponds to a pay grade of EG 13 TV-L.</p><h2>Unser Profil</h2><p>At the <strong>Chair of Thermodynamics of Mobile Energy Conversion Systems&nbsp;(TME)</strong> and the <strong>Center for Mobile Propulsion (CMP)</strong> under the direction of Prof. Dr.-Ing. (USA) Stefan Pischinger, research on all topics concerning the vehicle powertrain is conducted. Core focus is still the research on conventional combustion engine development like the implementation of innovative engine designs, fundamental research on more efficient combustion processes also in combination with alternative fuels or the improvement of the engine mechanics and aftertreatment systems. Additional research areas include virtual engine development, hybrid powertrains, electromobility as well as fuel cells and mechatronics for combustion engines. At any time research is closely associated with the ongoing development of intelligent methods for test procedures and engine calibration. The Chair of Thermodynamics of Mobile Energy Conversion Systems employs more than 260 scientific, technical and administrative employees as well as student assistants.</p><h2>Ihr Profil</h2><p>- University degree (Master or equivalent) in mechanical or electrical engineering with concentration on control technology or comparable disciplines is preferred<br>- Pronounced basic knowledge at the above-mentioned working priorities<br>- Proficient computer and software skills (MS Office, Matlab/Simulink, INCA etc.)<br>- Good English knowledge (written &amp; spoken)<br>- High degree of initiative, discipline and organizational skills<br>- Ability to work scientifically and independently<br>- Creativity, flexibility, team ability</p><h2>Ihre Aufgaben</h2><p>Mechanical or electrical engineer with the main focus on systems &amp; control technology.<br><br>- Set-up of simulation models for subsystems and the entire hybrid powertrain<br>- Set-up and testing of controls and control algorithms on research carriers inclusively V2V and V2X infrastructure<br>- Development of smart vehicle operation strategies with minimized energy demand<br>- Supervision of component test benches<br>- Supervision of engine test benches<br>- X-in-the-loop activities (i.e. HiL, MiL, SiL)<br>- Collaboration in the field of vehicle calibration <br><br></p><h2>Über uns</h2><p>RWTH is a certified family-friendly University. We support our employees in maintaining a good work-life balance with a wide range of health, advising, and prevention services, for example university sports. Employees who are covered by collective bargaining agreements and civil servants have access to an extensive range of further training courses and the opportunity to purchase a job ticket. <br>RWTH is an equal opportunities employer. We therefore welcome and encourage applications from all suitably qualified candidates, particularly from groups that are underrepresented at the University. All qualified applicants will receive consideration for employment and will not be discriminated against on the basis of national or ethnic origin, sex, sexual orientation, gender identity, religion, disability or age. RWTH is strongly committed to encouraging women in their careers. Female applicants are given preference if they are equally suitable, competent, and professionally qualified, unless a fellow candidate is favored for a specific reason.<br>As RWTH is committed to equality of opportunity, we ask you not to include a photo in your application.<br>You can find information on the personal data we collect from applicants in accordance with Articles 13 and 14 of the European Union's General Data Protection Regulation (GDPR) at <a href="http://www.rwth-aachen.de/dsgvo-information-bewerbung" target="_blank">http://www.rwth-aachen.de/dsgvo-information-bewerbung</a>.</p><h2>Besoldung / Entgelt</h2><p>EG 13 TV-L</p>

4 Application Engineer Jobs