{ "jobLocation" : { "@type" : "Place", "address" : { "@type" : "PostalAddress", "addressCountry" : "Germany", "addressLocality" : "Eggenstein-Leopoldshafen" } }, "applicantLocationRequirements" : { "@type" : "Country", "name" : "Germany" }, "jobLocationType" : "TELECOMMUTE", "hiringOrganization" : { "name" : "Carl Zeiss AG", "@type" : "Organization", "sameAs" : "" }, "identifier" : { "name" : "Internship - Soft-body Simulation, Simulation-Robot-Interface and Reinforcement Learning (f/m/x)", "@type" : "PropertyValue", "value" : "JR_1021785" }, "datePosted" : "2023-08-07", "employmentType" : "FULL_TIME", "title" : "Internship - Soft-body Simulation, Simulation-Robot-Interface and Reinforcement Learning (f/m/x)", "description" : "Motivation of the work Turning today’s research into tomorrow’s applications - together With a clear focus on user needs, the ZEISS Innovation Hub @ KIT explores new technology and application fields, enabling the transformation of ideas into innovations. Here, students, researchers, entrepreneurs, and ZEISS employees meet at eye level and practice an open-innovation culture.For our team of researchers and engineers, we seek for a student supporting our research and experiments for soft-body and tool-tissue simulations and Reinforcement Learning experiments Your role Work with SOFA, a simulation framework for soft body FEM simulations Enhance existing FEM models and algorithms for the simulation of anatomical structures, including tissue deformations caused during surgery Establish an interface between the simulation framework and real-world experiments - This involves the work on a robot control pipeline as well as computer vision modules Verify your simulation model with phantoms and post-mortem animal models using our lab setups Depending on your interest and experience: Implement a Reinforcement Learning framework for trajectory planning with tool-tissue interactions based on the FEM simulation Your profile A BSc and are enrolled in a masters’ program in mathematics, physics, informatics, engineering or similar Programming knowledge in at least one of the following: Python, C++, Matlab Knowledge of Simulation Open Framework Architecture (SOFA) is a plus Basic understanding of Reinforcement Learning is a plus Knowledge in one or more of the following fields: FEM Simulation, Reinforcement Learning, Computer Vision Excellent organization, problem-solving and communication (English and/or German) Passion for innovation and enthusiasm for new technologies as well as motivation to work in agile, interdisciplinary teams We offer Young, motivated team with a large and active student community Agile work environment with the possibility to work on various tasks for machine learning-based solutions Option for subsequent bachelor/master thesis Modern office culture with flexible working hours We are looking forward to receiving your application documents (cover letter, CV, certificates). Your ZEISS Recruiting Team: Franziska Gansloser, Selina Safradin Step out of your comfort zone, excel and redefine the limits of what is possible. That’s just what our employees are doing every single day - in order to set the pace through our innovations and enable outstanding achievements. After all, behind every successful company are many great fascinating people. In a spacious modern setting full of opportunities for further development, ZEISS employees work in a place where expert knowledge and team spirit reign supreme. All of this is supported by a special ownership structure and the long-term goal of the Carl Zeiss Foundation: to bring science and society into the future together. Join us today. Inspire people tomorrow. Diversity is a part of ZEISS. We look forward to receiving your application regardless of gender, nationality, ethnic and social origin, religion, philosophy of life, disability, age, sexual orientation or identity. Apply now! It takes less than 10 minutes.", "@context" : "http://schema.org", "@type" : "JobPosting" }