SENIOR AI MEDICAL IMAGING

The Centro Nacional de Investigaciones Cardiovasculares Carlos III (F.S.P) (CNIC) has been conceived to develop research of excellence, competitive and of international relevance in relation to cardiovascular diseases. The CNIC is a research center of 24,000 m², located in Madrid, with more than 6,000 m² for laboratories equipped with a state-of-the-art infrastructure and equipment.

CNIC leads the Project, AI POCVUS-REACT, “Artificial Intelligence-assisted point of care vascular ultrasound device for personalized cardiovascular prevention”.

We are looking for senior-level AI Developer with expertise in developing models for medical imaging applications. You will work on the development, optimization, and deployment of AI models, with a focus on improving the accuracy and efficiency of image analysis tools used in healthcare

This contract is funded by Mecanismo de Recuperación y Resiliencia de la Unión Europea-Next Generation, in the framework of the call “Solicitud de Proyectos de I+D de Excelencia en Inteligencia Artificial de la Secretaría de Estado de Digitalización e Inteligencia Artificial”

Functions:

• Leading the design, development, and deployment of advanced AI models; mentoring junior developers; owning large-scale projects.
• Develop, train, and optimize deep learning models for analyzing medical images.
• Integration of AI/ML models for real-time analysis and decision-making.
• Preprocess large datasets, perform data augmentation, and fine-tune model architectures for improved performance.
• Collaborate with medical professionals and researchers to understand domain-specific requirements.
• Optimize models for deployment in real-world applications, considering efficiency, speed, and accuracy.
• Document model development, experiments, and results for reproducibility.
• Contribute to the development of tools and pipelines for data processing, model training, and evaluation.

Mandatory Requirements:

1. Bachelor’s or Master’s degree in Computer Science, Biomedical Engineering, Data Science, or a related field.
2. At least 4 years of professional experience in AI/ML/Computer Vision, (2 years and 8 months for disabled people greater than 66% and 3 years and 4 months for disabled people greater than 33%).

Valuable Requirements:

• C1. Knowledge and experience in Python.
• C2. Strong expertise in Artificial Intelligence, particularly in training and fine-tuning deep learning models for image segmentation tasks. Strong understanding of supervised learning, data preprocessing, model optimization, and evaluation metrics relevant to improve performance.
• C3. Experience in training and optimizing AI models for integration into real-time applications, with a focus on low-latency inference, deployment on constrained systems.
• C4. Knowledge of Deep Learning architectures such as YOLO, UNet, nn-UNets, GANs, etc.
• C5. Knowledge and experience in Version Control. Familiarity with Git for code management and collaboration.
• C6. Knowledge and experience in Medical Imaging Knowledge. Prior experience with medical imaging datasets and an understanding of healthcare-specific challenges.
• C7. Experience in leadership and collaboration. Ability to lead and mentor junior developers, conduct code reviews, and work cross-functionally with healthcare professionals.
• C8. Underrepresentation of gender by category, in accordance with Action S1 of the 2021-2024 Equality Plan, POSITIVE ACTION IN CALLS FOR POSTS.
• C9. Interview (it will be partially conducted in English).

Positive action: a correction index of 1.5 is established for each year of experience in the evaluation of the number of years in those criteria where experience is evaluated, in the event that the person has a disability higher than 66% and 1.2 in the event that the person has a disability higher than 33%.

We offer:

• Competitive salary (estimated annual salary: 62.216,58 € + 25% variable €)
• Consolidated Research Center of international scientific relevance.
• Access to an infrastructure and advanced technologies.
• Integration into an excellent scientific environment.
• Immediate incorporation
• “Contrato de actividades científico-técnicas” de duración indefinida”, according to the article 23- bis “Ley de la Ciencia (texto refundido Ley 14/2011, de 1 de junio, de la Ciencia, la Tecnología y la Innovación)”, funded by project with Title: “Artificial Intelligence-assisted point of care vascular ultrasound device for personalized cardiovascular prevention (AI-POCVUS-REACT)”, to the call “Proyectos de I+D de Excelencia en Inteligencia Artificial del Ministerio de Transformación Digital y Función Pública”,  as long as the selected candidate complies with the legal requirements for the formalization of the contract in accordance with the Spanish labor law.

Selection Plan:

The RESOLUTION OF THE SECRETARIAT OF STATE FOR PUBLIC FUNCTION APPROVING THE COMMON ACTION CRITERIA IN THE SELECTIVE PROCESSES OF STATE PUBLIC SECTOR ENTITIES of April 11, 2022, establishes in point 6.1 that “Unless a specific regulation provides for the selective contest system, the selective system will be the contest-opposition”

In the case of CNIC, the specific regulations approved by the Foundation's board of trustees establish a selective competition system with an interview phase.

At least 3 candidates with the highest score (as long as they reach the minimum of 60 points as a sum of evaluation criteria (C1-C8) will be interviewed. The candidate with the highest score will be hired given the total score (C1-C9) is higher than 70 points.

Composition of the Selection Commission:

• Group Leader
• Group Researcher with high expertise in AI
• Research Office Coordinator
• Research Office Manager
• HR member

The CNIC guarantees, within its scope of action, the principle of equal access to employment, and may not establish any direct or indirect discrimination based on grounds of origin, including racial or ethnic origin, sex, age, marital status, religion or beliefs, political opinion, sexual orientation and identity, gender expression, sexual characteristics, trade union membership, social status, language within the State and disability, provided that the workers are fit to perform the work or job in question.

By participating in the selection process, the participant accepts that their data appear in the public resolutions of the selection process. Such resolutions (provisional list of admitted and excluded, definitive list of admitted and excluded and resolution of the process) are published on the CNIC website.

Scoring Criteria:

• C1. Knowledge and experience in Python (Experience will be assessed as a whole on the basis of the time/specialty ratio or according to the number of hours of accredited training). 20%
• C2. Strong expertise in Artificial Intelligence, particularly in training and fine-tuning deep learning models for image segmentation tasks. Strong understanding of supervised learning, data preprocessing, model optimization, and evaluation metrics relevant to improve performance. (Experience will be assessed as a whole on the basis of the time/specialty ratio or according to the number of hours of accredited training). 15%
• C3. Experience in training and optimizing AI models for integration into real-time applications, with a focus on low-latency inference, deployment on constrained systems (Experience will be assessed as a whole on the basis of the time/specialty ratio). 15%
• C4. Knowledge of Deep Learning architectures such as YOLO, UNet, nn-UNets, GANs, etc. (Assessment will be conducted according to the number of hours of accredited training). 10%
• C5. Knowledge and experience in Version Control. Familiarity with Git for code management and collaboration (Experience will be assessed as a whole on the basis of the time/specialty ratio or according to the number of hours of accredited training). 5%
• C6. Knowledge and experience in Medical Imaging Knowledge. Prior experience with medical imaging datasets and an understanding of healthcare-specific challenges. (Experience will be assessed as a whole on the basis of the time/specialty ratio or according to the number of hours of accredited training). 5%
• C7. Experience in leadership and collaboration. Ability to lead and mentor junior developers, conduct code reviews, and work cross-functionally with healthcare professionals (Experience will be assessed as a whole on the basis of the time/specialty). 5%
• C8. Underrepresentation of gender by category, in accordance with Action S1 of the 2021-2024 Equality Plan, POSITIVE ACTION IN CALLS FOR POSTS. 5%
• C9. Interview (it will be partially conducted in English). 20%