{"id":34,"date":"2025-03-06T11:43:40","date_gmt":"2025-03-06T11:43:40","guid":{"rendered":"https:\/\/aimedicine.rwth-aachen.de\/?page_id=34"},"modified":"2026-01-29T13:23:06","modified_gmt":"2026-01-29T13:23:06","slug":"team","status":"publish","type":"page","link":"https:\/\/aimedicine.rwth-aachen.de\/?page_id=34","title":{"rendered":"Team"},"content":{"rendered":"\t\t
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Meet the Team<\/h1>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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We are a young, diverse, and interdisciplinary team of scientists dedicated to developing deep learning methods for medical applications. Our goal is to extract valuable knowledge from clinical routine data and advance diagnostics and treatment in precision medicine.

We are based within the Department of Diagnostic and Interventional Radiology of RWTH Aachen in close proximity to the Netherlands and Belgium.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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Lab Leadership<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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\"Daniel<\/div>

Daniel Truhn<\/h4>
Daniel is a physicist, imaging scientist, and clinical radiologist with a dedicated focus on machine learning and magnetic resonance imaging. After studying physics at RWTH Aachen University and Imperial College in London, he continued to satisfy his thirst for knowledge by studying medicine at RWTH Aachen University. In 2013, he completed his MD thesis on the compatibility of positron emission tomography and magnetic resonance imaging and joined the Department of Diagnostic and Interventional Radiology (University Hospital Aachen) to become a board-certified clinical radiologist in 2019. Besides his clinical work, he pursued his research interests in machine learning as a fellow at the Institute of Imaging and Computer Vision (RWTH Aachen University) for two years before returning to the clinic where he currently leads the interdisciplinary research group \u201cAI in Medical Imaging\u201d. His research focuses on bringing machine learning-methods into clinical practice and on bridging the gaps between research possibilities and clinical applicability.<\/div>Read more<\/a><\/div><\/div><\/div><\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Senior Scientist<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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\"Sven<\/div>

Sven Nebelung<\/h4>
Sven is a clinical radiologist and imaging scientist focusing on clinically motivated imaging research that aims to refine image acquisition and post-processing methodologies in close collaboration with clinicians, clinical scientists, engineers, physicists, and imaging scientists. After studying medicine at RWTH Aachen University, he completed his MD thesis on cartilage tissue engineering. He joined the Department of Orthopedics (University Hospital Aachen) to receive orthopedic training during the surgical common trunk. After undertaking research at the Institute of Anatomy (RWTH Aachen University) in 2015, he entered Radiology specialist training at the Department of Diagnostic and Interventional Radiology (University Hospital Aachen). After completing a research stay at the Department of Diagnostic and Interventional Radiology (University Hospital D\u00fcsseldorf) from 2019 to 2021, he moved back to Aachen to lead the group. In 2022, he was board-certified as a radiologist and has been working as an attending physician I the Department of Diagnostic and Interventional Radiology (University Hospital Aachen) ever since, focusing his clinical work on MRI and musculoskeletal pathologies. His research is generously funded by the German Research Association (DFG) and funds from RWTH Aachen University. His recent publications are listed on Google Scholar and Pubmed. He also regularly reviews manuscripts for medical, technical, and interdisciplinary scientific journals. <\/div>Read more<\/a><\/div><\/div><\/div><\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Research Coordinator & IT Systems Administrator<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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\"Vera<\/div>
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Vera Winter<\/h4>Read more<\/a><\/div><\/div>
\"Juliana<\/div>
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Juliana de Castilhos<\/h4>Read more<\/a><\/div><\/div>
\"Jan<\/div>
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Jan Kerst<\/h4>Read more<\/a><\/div><\/div><\/div><\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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PhD Students<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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\"Patrick<\/div>
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Patrick Wienholt<\/h4>Read more<\/a><\/div><\/div>
\"Debora<\/div>
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Debora Jutz<\/h4>Read more<\/a><\/div><\/div>
\"Simon<\/div>
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Simon Westfechtel<\/h4>Read more<\/a><\/div><\/div>
\"Roman<\/div>
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Roman Vuskov<\/h4>Read more<\/a><\/div><\/div>
\"Mahta<\/div>
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Mahta Khoobi<\/h4>Read more<\/a><\/div><\/div>
\"Hanna<\/div>
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Hanna Kreutzer<\/h4>Read more<\/a><\/div><\/div>
\"Eneko<\/div>
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Eneko Cornejo Merodio<\/h4>Read more<\/a><\/div><\/div>
\"Marvin<\/div>
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Marvin Gazibari\u0107<\/h4>Read more<\/a><\/div><\/div>
\"Frederik<\/div>
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Frederik Hauke<\/h4>Read more<\/a><\/div><\/div>
\"Paul<\/div>
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Paul Ehrlich<\/h4>Read more<\/a><\/div><\/div>
\"Zihao<\/div>
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Zihao Zhao<\/h4>Read more<\/a><\/div><\/div>
\"Daniel<\/div>
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Daniel Geiger<\/h4>Read more<\/a><\/div><\/div>
\"Kilian<\/div>
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Kilian Gildemeister<\/h4>Read more<\/a><\/div><\/div><\/div><\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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\nPostdoctoral Researchers\n<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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\"Soroosh<\/div>
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Soroosh Tayebi Arasteh<\/h4>Read more<\/a><\/div><\/div>
\"Dennis<\/div>
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Dennis Eschweiler<\/h4>Read more<\/a><\/div><\/div><\/div><\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Student Assistants<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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\"Lena<\/div>
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Lena Kotowski<\/h4>Read more<\/a><\/div><\/div>
\"Konstantin<\/div>
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Konstantin \u00dcffing<\/h4>Read more<\/a><\/div><\/div>
\"Aleksander<\/div>
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Aleksander Lichev<\/h4>Read more<\/a><\/div><\/div>
\"Sophie<\/div>
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Sophie Caselitz<\/h4>Read more<\/a><\/div><\/div>
\"Inga<\/div>
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Inga Schneider<\/h4>Read more<\/a><\/div><\/div>
\"Celina<\/div>
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Celina Helbig Vital<\/h4>Read more<\/a><\/div><\/div>
\"Nikol<\/div>
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Nikol Ignatova<\/h4>Read more<\/a><\/div><\/div><\/div><\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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Alumni<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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\"Tianyu<\/div>
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Tianyu Han<\/h4>Read more<\/a><\/div><\/div>
\"Firas<\/div>
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Firas Khader<\/h4>Read more<\/a><\/div><\/div>
\"Gustav<\/div>
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Gustav M\u00fcller-Franzes<\/h4>Read more<\/a><\/div><\/div>
\"Alexander<\/div>
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Alexander Hermans<\/h4>Read more<\/a><\/div><\/div><\/div><\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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Yes, you can join us.\u200b<\/h3>

We are always seeking talented and motivated individuals to join our dynamic and interdisciplinary team. If you are a passionate student or researcher interested in the exciting field of AI applications in medicine, we would love to hear from you!<\/p>

We offer various opportunities for collaboration, including:<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Master Thesis<\/h4>

If you are a high-achieving master’s student with a strong academic background in computer science, physics, electrical engineering, or a related field, and have a keen interest in medical AI, we encourage you to consider pursuing your master thesis with us. This is also an excellent opportunity for us to get to know you and potentially follow-up with a career as a PhD student in our lab.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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PhD Thesis<\/h4>

For exceptional candidates who have completed their master’s degree with above-average grades and aspire to conduct cutting-edge research in AI for medical imaging and precision oncology, we provide a stimulating environment to pursue your doctoral studies.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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If you believe you have the skills, passion, and academic excellence to contribute to our mission of advancing AI in medicine, please don’t hesitate to reach out to us. Send your CV, a brief statement of your research interests, and relevant academic transcripts to our email.<\/strong><\/p>

Please also try to solve the riddle below – you will get bonus points, if you solve it! We look forward to hearing from you!<\/strong><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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Can you solve this riddle?<\/h4>

Fill all edges of this graph with the number 1 to 24. Each number can only be used once. The numbers 7, 12, 20, and 24 are already given. The nodes provide additional constraints:<\/p>

The number inside this node denotes the sum of all edges directly connected to it.<\/p>

There exists a non-intersecting path starting from this node with the sum of the weights of the edges along that path equaling the number within this node. Multiple numbers refer to multiple paths (may overlap).<\/p>

Once you filled all edges find the shortest weighted path from the scientist to the AI-chip and convert it to letters (1=A, 2=B etc.) to reveal the secret message.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tSubmit your answer<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"

Meet the Team We are a young, diverse, and interdisciplinary team of scientists dedicated to developing deep learning methods for medical applications. Our goal is to extract valuable knowledge from clinical routine data and advance diagnostics and treatment in precision medicine. We are based within the Department of Diagnostic and Interventional Radiology of RWTH Aachen […]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"footnotes":""},"class_list":["post-34","page","type-page","status-publish","hentry"],"acf":[],"_links":{"self":[{"href":"https:\/\/aimedicine.rwth-aachen.de\/index.php?rest_route=\/wp\/v2\/pages\/34","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/aimedicine.rwth-aachen.de\/index.php?rest_route=\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/aimedicine.rwth-aachen.de\/index.php?rest_route=\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/aimedicine.rwth-aachen.de\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/aimedicine.rwth-aachen.de\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=34"}],"version-history":[{"count":205,"href":"https:\/\/aimedicine.rwth-aachen.de\/index.php?rest_route=\/wp\/v2\/pages\/34\/revisions"}],"predecessor-version":[{"id":1450,"href":"https:\/\/aimedicine.rwth-aachen.de\/index.php?rest_route=\/wp\/v2\/pages\/34\/revisions\/1450"}],"wp:attachment":[{"href":"https:\/\/aimedicine.rwth-aachen.de\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=34"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}