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It's a good feeling to know you're doing your best with purpose every day. At Artivion, we manufacture high-quality products and solutions for the treatment of aortic diseases. Together with surgeons worldwide, we save lives. In doing so, we rely on the strengths of each and every employee. Your strength counts, too: As an important link in the chain, you make a contribution to saving lives together with us. Bring your strengths and let us grow together.¿Es este el puesto que está buscando? Si es así, siga leyendo para obtener más detalles y no olvide enviar su solicitud hoy mismo.We are hiring aClinical Research Associate III – Home-Based in Spain (Spanish speaking candidates in France are also welcome)Your StrengthMinimum of 4 years of advanced experience in clinical research monitoringIn-depth knowledge of regulations and guidelines related to clinical trials involving human subjects (e.G., ISO 14155, GCP, MDR, EU, FDA)Ability to independently manage 10–15 study sites from start-up through close-outExcellent communication skills for site interaction, training, and issue resolutionStrong collaboration and mentorship abilities, with a passion for supporting and guiding junior team membersHands-on experience with monitoring systems, source data verification, and compliance trackingStrong organizational skills with the ability to manage multiple priorities in a dynamic environmentWillingness to travel regularly for site visits and investigator meetings across France and SpainBased in Spain (candidates from France may be considered in case a candidate lives nearby the Spain/France border and eager to do cross border monitoring)Fluent communication in English and Spanish (Catalan is preferred, French optional)Your ContributionIndependently manage all phases of clinical trial site activities, including site identification, initiation, monitoring, and close-outConduct monitoring visits in accordance with study protocols, GCP, and applicable regulatory requirementsAct as the primary contact for investigational sites, ensuring compliance and providing ongoing supportBuild and maintain strong relationships with investigators, study coordinators, and site personnelIdentify study risks, recommend solutions, and ensure timely resolution of site-related issuesPerform source data verification and data review to ensure patient safety, protocol compliance, and data integrityConduct site training, initiation visits, and support audit and inspection readinessCollaborate closely with Clinical Operations, Data Management, Medical Affairs, and other cross-functional teamsSupport investigator meetings, coordinator meetings, and deliver presentations or training sessions when requiredMentor junior CRAs and contribute to process improvements and best practicesParticipate in CAPA activities, quality initiatives, audits, and continuous improvement effortsOur StrengthA mission-driven company focused on saving livesInternational and collaborative MedTech environmentHybrid working model with flexibilityOpportunities for growth and professional developmentInnovative products and meaningful clinical impactContactApply now and join the Artivion team. xhfqzwm We look forward to receiving your application documents in English through our online application system.Brian RussoT: JOTEC GmbH, a wholly owned subsidiary of Artivion, Inc.Lotzenäcker 23, 72379 Hechingen

Job SummaryThe successful candidate will join the Germans Trias i Pujol Research Institute (IGTP) as part of a multidisciplinary team developing AI‑based computer vision systems for surgical instrument recognition. The project is carried out in collaboration with HealthTech Innovations and is deployed on a robotic platform used in the central sterilization unit and operating rooms of the Hospital Universitari Germans Trias i Pujol. The role focuses on the design, training and optimization of computer vision and deep learning algorithms, covering the full pipeline from data acquisition to model deployment. Technical autonomy is required, with responsibility for code, model iterations, architecture decisions and integration with the robotic platform.Main Responsibilities- Lead the development of the AI‑based surgical instrument recognition system, with direct responsibility for design, training and performance of its computer vision and machine learning components.- Design and develop computer vision pipelines for surgical instrument detection, classification and tracking, covering the full lifecycle from data acquisition and preprocessing to model training, evaluation and deployment.- Write, optimize and maintain production‑quality code, ensuring robustness, scalability and reproducibility of AI models.- Train and fine‑tune machine learning and deep learning models, selecting appropriate architectures, defining evaluation metrics and implementing strategies to improve accuracy and generalization in real hospital environments.- Generate datasets, define labeling strategies and data augmentation techniques, and iterate on models based on validation results.- Collaborate with the robotics engineering team to support integration of the AI/computer vision modules into the robotic platform, focusing on the perception side of the perception‑action loop.- Test and validate the system in the central sterilization unit and operating room, analyze performance, identify limitations and propose technical improvements.- Document algorithms, code and experimental results to support regulatory processes and scientific dissemination.Qualifications and Experience- Degree in Computer Science, Telecommunications Engineering, Data Science, Artificial Intelligence, Mathematics/Physics with a computational focus, or a related technical field.- Master’s degree or specialized training in Artificial Intelligence, Machine Learning, Deep Learning or Computer Vision; or equivalent professional experience.- Strong hands‑on experience developing computer vision and deep learning systems for real‑world applications (object detection, segmentation, classification, tracking).- Proficiency in Python and practical experience in at least one major deep learning framework (PyTorch or TensorFlow).- Experience with OpenCV and the full model lifecycle—dataset generation, labeling, augmentation, training, evaluation and iterative optimization.- Comfortable operating in multidisciplinary environments, with the ability to work closely with clinical staff.- Fluency in Spanish (mandatory); Catalan valued as an asset. Good level of English for technical documentation and collaboration.- Strong problem‑solving skills, autonomy, proactive attitude and genuine ownership of technical decisions.- Availability to commute regularly to the Hospital Universitari Germans Trias i Pujol or to the HealthTech Innovations offices.Additional Qualifications (Optional)- Knowledge of C/C++ and robotics middleware (e.G., ROS).- Prior exposure to robotic perception systems or integration of AI components into a robotic platform.Benefits- Indefinite contract under science law linked to Project CPP2024‑011704, fully funded by MICIU/AEI/FEDER and the EU.- Immediate incorporation into a highly innovative applied research and development project with direct impact on real clinical environments.- Full‑time position with a 39‑hour work week and flexible working schedule.- Hybrid model allowing partial remote work with regular on‑site collaboration sessions.- 23 days of paid annual leave, plus 5 additional days for personal matters, 2 days for Easter and 2 days for Christmas.#J-18808-Ljbffr

ph3Job Summary /h3pThe successful candidate will join the Germans Trias i Pujol Research Institute (IGTP) as part of a multidisciplinary team developing AI‑based computer vision systems for surgical instrument recognition. The project is carried out in collaboration with HealthTech Innovations and is deployed on a robotic platform used in the central sterilization unit and operating rooms of the Hospital Universitari Germans Trias i Pujol. The role focuses on the design, training and optimization of computer vision and deep learning algorithms, covering the full pipeline from data acquisition to model deployment. Technical autonomy is required, with responsibility for code, model iterations, architecture decisions and integration with the robotic platform. /ph3Main Responsibilities /h3ulliLead the development of the AI‑based surgical instrument recognition system, with direct responsibility for design, training and performance of its computer vision and machine learning components. /liliDesign and develop computer vision pipelines for surgical instrument detection, classification and tracking, covering the full lifecycle from data acquisition and preprocessing to model training, evaluation and deployment. /liliWrite, optimize and maintain production‑quality code, ensuring robustness, scalability and reproducibility of AI models. /liliTrain and fine‑tune machine learning and deep learning models, selecting appropriate architectures, defining evaluation metrics and implementing strategies to improve accuracy and generalization in real hospital environments. /liliGenerate datasets, define labeling strategies and data augmentation techniques, and iterate on models based on validation results. /liliCollaborate with the robotics engineering team to support integration of the AI/computer vision modules into the robotic platform, focusing on the perception side of the perception‑action loop. /liliTest and validate the system in the central sterilization unit and operating room, analyze performance, identify limitations and propose technical improvements. /liliDocument algorithms, code and experimental results to support regulatory processes and scientific dissemination. /li /ulh3Qualifications and Experience /h3ulliDegree in Computer Science, Telecommunications Engineering, Data Science, Artificial Intelligence, Mathematics/Physics with a computational focus, or a related technical field. /liliMaster’s degree or specialized training in Artificial Intelligence, Machine Learning, Deep Learning or Computer Vision; or equivalent professional experience. /liliStrong hands‑on experience developing computer vision and deep learning systems for real‑world applications (object detection, segmentation, classification, tracking). /liliProficiency in Python and practical experience in at least one major deep learning framework (PyTorch or TensorFlow). /liliExperience with OpenCV and the full model lifecycle—dataset generation, labeling, augmentation, training, evaluation and iterative optimization. /liliComfortable operating in multidisciplinary environments, with the ability to work closely with clinical staff. /liliFluency in Spanish (mandatory); Catalan valued as an asset. Good level of English for technical documentation and collaboration. /liliStrong problem‑solving skills, autonomy, proactive attitude and genuine ownership of technical decisions. /liliAvailability to commute regularly to the Hospital Universitari Germans Trias i Pujol or to the HealthTech Innovations offices. /li /ulh3Additional Qualifications (Optional) /h3ulliKnowledge of C/C++ and robotics middleware (e.g., ROS). /liliPrior exposure to robotic perception systems or integration of AI components into a robotic platform. /li /ulh3Benefits /h3ulliIndefinite contract under science law linked to Project CPP2024‑ , fully funded by MICIU/AEI/FEDER and the EU. /liliImmediate incorporation into a highly innovative applied research and development project with direct impact on real clinical environments. /liliFull‑time position with a 39‑hour work week and flexible working schedule. /liliHybrid model allowing partial remote work with regular on‑site collaboration sessions. /lili23 days of paid annual leave, plus 5 additional days for personal matters, 2 days for Easter and 2 days for Christmas. /li /ul /p #J-18808-Ljbffr

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