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Research assistant / hiwi / master thesis machine learning in microfluidics applications (f/m/d)

Betzenhausen
Abschlussarbeit
Hahn-Schickard-Gesellschaft für angewandte Forschung e.V.
Assistant
Inserat online seit: 27 Mai
Beschreibung

Vision to Products Welcome to Hahn-Schickard: The research center for innovative microsystems technology. With a team of over 300 employees, we transform ideas into cross-industry solutions - from conception to production at four locations in Baden-Württemberg. At our Freiburg site, the emphasis is on developing analytical solutions in microsystems technology, particularly for point-of-care diagnostics. For a research project in the field of microfluidics, our Laboratory Automation group in Freiburg is looking for a Research Assistant / HiWi / Master Thesis Machine Learning in Microfluidics Applications (f/m/d) Your Tasks Tackle exciting challenges in the fields of Machine Learning and Microfluidics, ranging from the detection of microtumors to the volume estimation of dispensing systems. Take a central role in annotating images from our extensive dataset, with a specific focus on microscopic particles, notably three-dimensional microtumors. Collaborate within an interdisciplinary research project, contributing to the advancement of scientific understanding in microfluidics and laboratory automation. Contribute significantly to the training and validation of an AI system, which is crucial for both enhancing the automated arrangement of viable microtumors within multiwell plates and improving the volume estimation of jets. Engage closely with our dedicated researchers, collectively pushing the boundaries of what’s possible in our field. Your profile Bachelor’s degree in Computer Science/ Engineering or a related field. Experience in image annotation or a similar role, particularly with microscopic images. Familiarity with machine learning processes and a keen interest in AI applications in the scientific field. Excellent collaboration skills, with a proactive approach to interdisciplinary teamwork. Creative thinking and problem-solving abilities. Potential for a thesis in machine learning. In this case, proficiency in the Python programming language and first experiences in machine learning are essential. Proficient in either English or German. Our offer to you Being part of a dynamic and interdisciplinary team, thriving within an environment that nurtures innovation and collaboration. Access to cutting-edge facilities, featuring well-equipped laboratories at your disposal. An attractive workplace conveniently located on the campus of Albert-Ludwigs-Universität Freiburg Future-proof career: a wide range of possible assignments during and after your studies Flexible working hours & duration Training and development: Benefit from our expert guidance and support Health and lifestyle: Participation in first-class health programs such as Hansefit and team events Allowance for meals in the canteen and surrounding area Mobility support: monthly subsidy for public transportation Your Application If you are interested in this topic please apply directly online with the following complete documents (cover letter/resume/certificates and possibly a list of publications), preferentially in one single PDF-document, quoting the internal reference number 25/3630/16 If you have any technical questions, please contact Ms. Dr. Sabrina Kartmann in advance at 49 761/203 73287 or via Mail: Sabrina.Kartmann@hahn-Schickard.de As we always evaluate your applications personally, we ask for your patience Ihre Ansprechpartnerin Frau Antigoni Zouridaki Kontakt Hahn-Schickard-Gesellschaft für angewandte Forschung e.V. Georges-Köhler-Allee 103 79110 Freiburg im Breisgau Personal-FR@Hahn-Schickard.de 0761 203 73200

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