What makes you stand out You have several years of experience leading teams in a payments, IT, or platform operations environment.You bring solid expertise in payment processing, ideally in the areas of card acceptance, authorization systems, or payment schemes.You hold a completed degree in Computer Science, Business Informatics, Business Administration, or a comparable qualification.You have experience operating highly available 24/7 systems as well as in incident and provider management.You also have a strong technical understanding of complex system architectures, integrations, and data flows.You have proven experience managing external service providers and leading complex, cross-functional projects.You are able to develop and implement technical concepts, feasibility analyses, and innovative solution approaches.You work in a structured and analytical manner and stand out through strong communication and stakeholder management skills.Very good German and English language skills, both written and spoken, complete your profile.
Experience with OpenCL is required, particularly for implementation on heterogeneous compute platforms such as Qualcomm architectures. Strong background in digital signal processing and statistical signal processing. Experience in HF technology and/or antenna design.
Vacancy at the Berlin University for a professorship (W2) in the field of Health Informatics, which may and should also initiate its own research projects. A Bachelor's programme in Computer Science in Culture and Health and a Master's programme in Applied Computer Science are offered.The teaching assignment is in Bachelor's and Master's degree programmes of the department at the University in Berlin.
What makes you stand out You have successfully completed a degree in Business Informatics, Computer Science, Business Administration, or a comparable qualification. You bring solid knowledge of payment, card and transaction processing, or electronic payment systems.You have a strong technical understanding of payment system architectures, authorization systems, and interfaces to external service providers, and you have experience in analyzing, specifying, and implementing product requirements.
Your Profile - Qualifications • Bachelor’s/Master’s/PhD in Computer Science, Applied Mathematics, Engineering, or related field. • Strong background in machine learning, deep learning. • Proven experience with 3D graphics, computational geometry (meshes, point clouds, surface reconstruction) or computer vision • Proficiency in Python, C++, and ML frameworks (TensorFlow, PyTorch). • Experience with medical imaging data (CT, CBCT, intraoral scans) is a plus. • Full professional proficiency in English is required Preferred Skills • Familiarity with GANs, diffusion models, or neural rendering for material reconstruction. • Familiarity with biomedical applications. • Strong problem-solving skills and ability to work in interdisciplinary teams. • Excellent communication and documentation abilities. • Large language modules (plus) What We Offer • Opportunity to work on cutting-edge applications in digital dentistry and orthodontics. • Collaborative environment with experts in ML, graphics, and healthcare. • Competitive salary and benefits package. • Career growth in a rapidly evolving field.
Rethink Retail: Stay in front of emerging trends, analyze, and design next-gen business processes across omnichannel environments. What You Bring Education: Degree in Computer Science, Information Technology, Management Information Systems, or relevant discipline. Experience: Strong experience in the Central/Latin America retail market and POS process knowledge.
Principal Accountabilities: Collaboration in projects of the European Data Science & Advanced Analytics Team.Concept, design, development and execution of complex innovative AI/Machine Learning solutions as well as execution and implementation of concept studies using advanced statistical methods.Development of deep learning models for structured medical concept extraction from unstructured data.Productionalization of machine learning algorithms in Big Data platforms.Application of modern data mining and machine learning techniques in connection with Healthcare Big Data to identify complex relationships and link heterogeneous data sources.Advanced usage of Large Language Models for summarization, chatbot, entity extraction etc.Develop foundational Deep Learning Models for assets and patients.Builds and trains new production grade algorithms that can learn from complex, high dimensional data to uncover patterns from which machine learning models and applications can be developed. Our Ideal Candidate Will Have: Master’s degree in Computer Science, Mathematics/Statistics, Economics/Econometrics or related field.Substantial years of professional experience in quantitative data analysis or PhD with at least 1 year of relevant professional experience with research in machine learning algorithms.Very good knowledge and in depth understanding of Machine Learning methods, both classical and deep learning models.Relevant experience with Natural Language Processing (NLP) models for extracting structured concepts from unstructured free text, including the design, training, and evaluation of information‑extraction pipelines.Very strong technical capability in Python, SQL, Hadoop ecosystem.Experience applying AI/Machine Learning methods to business questions.Very good knowledge of the higher statistical and econometric methods in theory and practice.Experience with handling Big Data.Ability to write clean, reusable, production-level codeExcellent communication skills (written and oral) including technical aspects of a project, ability to develop usable documentation, results interpretation and business recommendations.Strong analytic mindset and logical thinking capability, strong QC mindset.Knowledge of pharmaceutical market and experience with pharmaceutical data (medical, hospital, pharmacy, claims data) would be a plus, but not a must.Self-responsible for managing projects.Fluency in German & English.
Review operational costs, negotiate contracts with vendors, and manage vendor relationships. Requirements: Bachelor's degree in Engineering, Computer Science, or a related field. HV Authorised Person (Experienced with HV Systems) Electrical/Mechanical Engineering HNC or HND (Successfully completed apprenticeship in either) C&G Pts. 1 & 2, equivalent or exceeds. 17th Edition IEE: Wiring and Installation (Ability to attain 18th Edition through additional training) C&G 2391 test and inspection; BS 7671:2001 for inspection, testing and certification.