.Research Data Engineer for the Health DomainResearch Data Engineer for the Health Domain The Digital Health and Biomedical Technologies Department is a source of innovative solutions in the biomedical sector, with applications of technologies such as biomedical image analysis, biomedical simulation, decision support systems based on artificial intelligence approaches, computer-assisted surgery and many others.We are looking for motivated candidates for our Digital Health team with an applied research profile and demonstrated experience in data engineering and software development for the digital health domain. For this position, experience in the development of digital biobanks and/or other types of (research) data-sharing platforms will be valued, covering aspects such as data ingestion, preparation, integration, and harmonisation and the related software developments and Big Data platforms. Previous experience in the application of artificial intelligence techniques in this context will be also valued.Candidates must show a proactive attitude toward applied research, showing an excellent scientific and/or technical record on the offered topic, a proven teamwork capacity and a commitment to understanding the needs of clients and project partners, as well as the ones coming from other projects and initiatives on this research line. Candidates should have also the necessary programming skills to convert their knowledge into actual software solutions.Candidates must have:Education: At least a M.Sc. degree in computer science, telecommunications or related fields. Candidates about to complete their doctoral training will also be considered.Experience :Digital Biobank Interoperable architecture definition and developmentSecure data-sharing and processing environment solutionsFederated learning frameworksClinical, molecular, and other health-determinants data managementMetadata cataloguing and existing data models (e.G., OMOP, HL7, FHIR)Python web-frameworks development and deploymentSkills in data preparation / science programming languages e.G., R, Python (SciKit) and implementations focussed on single and distributed computing.Experience in the design and development of timely asynchronous data processing systems (batch, streaming) in both Big Data and non-Big Data contexts. Example technologies include Kafka, Storm, Spark and Celery.DevOPs Knowledge of different cloud service providers at their different service offerings (e.G., IaaS, PaaS): Amazon Web Services, Google Cloud Platform, Microsoft Azure.Microservices approach, container encapsulation and orchestration technologies: Docker, Kubernetes.Experience in Linux work environments (scripting, service management, performance analysis and tuning)DevOp automatization tools: Gitlab CI/CD, Jenkins.We value candidates:E xperience with machine learning, deep learning and/or generative models will be valued
