51514MKP - Senior AI, Data Infrastructure & CADAD Project Manager (VALL D'HEBRON RESEARCH INSTITUTE)
Barcelona ActivaCatalonia, SpainHace 4 días
Descripción del trabajoLead the development and deployment of AI-driven models, including deep learning, NLP, and federated learning. Integrate AI solutions into clinical workflows, ensuring compliance with GDPR, CE marking, and medical device regulations. Develop and optimize scalable data pipelines for efficient healthcare data management. Oversee AI-driven ISO 27001 and ENS certification processes for clinical applications. Work closely with researchers, clinicians, and IT specialists to drive data-driven healthcare innovations. Establish privacy-preserving AI models through federated learning across distributed healthcare networks. Mentor and support junior project managers, engineers, and data scientists. Define project timelines, deliverables, and reporting structures for AI initiatives. Coordinate multiple data-driven projects, aligning them with institutional objectives. Supervise execution of AI and data science projects, ensuring research and regulatory alignment. Maintain oversight of project documentation, approval processes, and compliance with legal agreements and EU AI Act. Represent VHIR in AI collaborations, academic partnerships, and conferences. Ensure data security, quality, and governance throughout the AI & Data Science project lifecycle. Be active part of AI-driven medical solution certification and regulatory approval processes. Oversee the procurement, deployment, security and maintenance of hardware / software solutions for data processing and AI model training. Supervise the design, implementation and management of high-performance on-premise our cloud computing environments supporting AI research and distributed computing. Integrate data warehouses, data lakes, and real-time processing systems for large-scale healthcare AI projects. Implement and manage big data frameworks (Apache Spark, Hadoop, Kafka, Cassandra) and cloud-based solutions (AWS Glue, Google Cloud Dataflow). Ensure compliance with healthcare data security regulations (GDPR, OpenEHR). Optimize and manage containerized AI deployments (Docker, Kubernetes) for scalable applications. Monitor and enhance on-premise or cloud data infrastructure for performance and scalability. Provide technical leadership in evaluating and adopting new tools for AI-driven healthcare innovation. Contract : open-ended contract linked to project Full-time position : 40h / week Starting date : immediate Gross annual salary : 38.000 - 42.000. Remuneration will depend on experience and skills. Salary ranges are consistent with our Collective Agreement pay scale. Working hours : Flexible, from 8 : 00 - 10 : 00 till 17 : 00 - 19 : 00, Monday - Thursday. Fridays from 8 : 00 to 15 : 00. July and August, from 8 : 00 to 15 : 00. Incorporation into Vall d'Hebron Research Institute (VHIR), a public sector institution that promotes and develops biomedical research, innovation, and teaching at Vall d'Hebron University Hospital (HUVH), the biggest hospital in Barcelona and the largest of Catalan Institute of Health (ICS). A scientific environment of excellence and a highly dynamic setting where innovative biomedical projects are continuously developed. Opportunities for leadership in AI-driven healthcare initiatives. Continuous learning and a wide range of responsibilities within a stimulating work environment. Individual training opportunities. 23 days of holidays + 9 personal days. Flexible Remuneration Program and access to corporate benefits. The chance to contribute to groundbreaking AI research in a globally recognized healthcare institution. Bachelor's or Master's degree in Health Sciences, Computer Science, Data Science, Bioinformatics, Artificial Intelligence, Information Technology, Telecommunications, or related fields. PhD in Data Science, AI, Computer Science, Bioinformatics, or a related field. Certification in data center management or cloud platforms (e.g., AWS, Azure, Google Cloud). 4+ years of experience in AI, data science, data infrastructure, or clinical data project management, preferably in healthcare or life sciences. Strong knowledge of SQL / NoSQL databases, data lakes, ETL pipelines, and data integration methodologies. Proficiency in programming languages such as Python, R, Java, or Scala for data processing and automation. Experience deploying AI models in production environments using frameworks such as TensorFlow, PyTorch, and Scikit-Learn. Knowledge of cloud platforms (AWS, Azure, Google Cloud) and containerization tools (Docker, Kubernetes). Familiarity with project management methodologies (PMP, Agile, ITIL) and experience leading cross-functional teams. Expertise in GDPR, regulatory frameworks, and healthcare data security standards. Fluency in Spanish and English (business level). Experience with federated learning environments and distributed AI training. Knowledge of OMOP, OpenEHR, and healthcare data security frameworks. Expertise in high-performance computing (HPC) and real-time data processing architectures. Experience with big data technologies such as Hadoop, Spark, Kafka, and Cassandra. Strong publication record in peer-reviewed journals or AI research contributions. Proven ability to collaborate across academic, healthcare, and industry sectors. Expertise in data center implementation, including the design, procurement, and deployment of hardware for data storage, computing, networking, security, and redundancy Expertise with OMOP, OpenEHR, and healthcare data security. Experience with cloud-native data warehouses like Snowflake, Google BigQuery, Microsoft Azure SQL or Amazon Redshift. Familiarity with data pipeline architectures, including Lambda and Kappa architectures, and the ability to implement batch and real-time data processing techniques. Experience in designing and maintaining data warehouses and real-time data processing architectures (Lambda, Kappa architectures). Experience with ETL tools like Apache Nifi, Talend, Informatica, Microsoft SSIS or AWS Glue. Experience leading cross-functional teams. Experience managing budgets and procurement for IT infrastructure projects. Proficiency in scripting and automation for infrastructure management using languages such as Bash or PowerShell. Knowledge of containerization and orchestration tools (e.g., Docker, Kubernetes). Experience with high-performance computing (HPC) environments and data pipeline frameworks like Apache Airflow. Fluency in Catalan (business level).
This position is part of the BIOINFORMATICS JOBMARKETPLACE organized by Barcelona Activa together with CERCA (Catalunya Research Centers) and BIB (Bioinformatics of Barcelona), on Thursday, November 13, from 10 : 00 a.m. to 1 : 00 p.m.
The VALL D'HEBRON RESEARCH INSTITUTE is looking for this postion : Senior AI , Data Infrastructure & CADAD Project Manager
Only those who meet the requirements requested by the company will be notified.
Attendance and details will be confirmed by email.
Roles and responsabilities :
VHIR is at the forefront of biomedical research, innovation, and digital transformation, collaborating with Vall d'Hebron University Hospital (HUVH), the largest hospital in Catalonia.
We are seeking a Senior AI, Data Infrastructure & CADAD Project Manager to lead and coordinate AI-driven healthcare research projects, ensuring seamless integration of clinical data, AI model development, and high-performance infrastructure. This role is crucial for managing project execution, data governance, and strategic planning while collaborating with multidisciplinary teams to implement AI solutions in healthcare.
CADAD & Project Management
- Oversee and manage the Clinical Data Science Access for Secondary Use Committee (CADAD), ensuring compliance with legal and ethical guidelines.
- Facilitate communication between researchers and CADAD, identifying and overseeing project approvals.
- Manage the collection, processing, and secondary use of clinical data while ensuring GDPR and healthcare data privacy compliance.
- Plan, monitor, and execute CADAD projects, ensuring timely deliverables and compliance.
- Bridge the gap between technical teams, data science architects, and clinical stakeholders to enable effective AI-driven project execution.
- Utilize project management frameworks (PMP, Agile, ITIL) to streamline AI and data science projects.
Data Science & AI Development
Project & Team Leadership
Infrastructure & Data Engineering
Conditions :
Benefits :
Requisits : Required :
Desired :
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Senior Infrastructure • Catalonia, Spain
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