3D MODELING SPECIALIST-MEDICAL DATA (VASCULAR FOCUS)

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 seeking a skilled 3D Modeling Specialist with expertise in creating accurate and detailed 3D models from medical data. The ideal candidate will have strong Python programming skills, and proficiency in 3D modeling software. French language skills are a plus for communication within international teams.

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:

• Develop and refine high-quality 3D models from medical imaging data, with a focus on vascular structures combining information from imaging and external tracking devices, gyroscopes and accelerometers.
• Integrate 3D models for real time visualization in ad-hoc software analysis.
• Automate data processing workflows and model generation using Python for handling large datasets.
• Work with cross-disciplinary teams to support model deployment in healthcare applications, including AI integration.

Mandatory Requirements:

1. Bachelor’s or Master’s degree in Biomedical Engineering, Computer Science, Medical Physics, or a related field.

Valuable Requirements:

• C1. Experience in 3D Modeling Software. Proficiency in tools such as MeshLab, or Amira for medical data visualization and model creation.
• C2. Experience in Python Programming. Experience in automating 3D data processing, working with libraries like PyMesh, VTK, or Mayavi for model manipulation.
• C3. Knowledge and experience in Medical Data Formats (medical imaging formats like DICOM and techniques for reconstructing 3D models from 2D image data)
• C4. Experience in Image Segmentation. Experience in segmentation, registration and annotation techniques to extract anatomical structures from medical images
• C5. Knowledge and experience in Visualization. Ability to create detailed visual representations of vascular structures
• C6. Knowledge and experience in Data Processing. Knowledge of pre- and post-processing of imaging data, including noise reduction, filtering, and mesh generation.
• C7. Knowledge of languages. Proficiency (level C2 CEFR scales) in French and/or English is highly valued for communication with international collaborators.
• C8. Experience in a clinical or research environment
• C9. Underrepresentation of gender by category, in accordance with Action S1 of the 2021-2024 Equality Plan, POSITIVE ACTION IN CALLS FOR POSTS.
• C10. 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 (annual salary estimated: 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 de la 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 65 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 75 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. Experience in 3D Modeling Software. Proficiency in tools such as MeshLab, or Amira for medical data visualization and model creation (Experience will be assessed as a whole on the basis of the time/specialty ratio). 15%
• C2. Experience in Python Programming. Experience in automating 3D data processing, working with libraries like PyMesh, VTK, or Mayavi for model manipulation (Experience will be assessed as a whole on the basis of the time/specialty). 10%
• C3. Knowledge and experience in Medical Data Formats (medical imaging formats like DICOM and techniques for reconstructing 3D models from 2D image data) (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). 10%
• C4. Experience in Image Segmentation. Experience in segmentation, registration and annotation techniques to extract anatomical structures from medical images (Experience will be assessed as a whole on the basis of the time/specialty ratio). 10%
• C5. Knowledge and experience in Visualization. Ability to create detailed visual representations of vascular structures (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). 10%
• C6. Knowledge and experience in Data Processing. Knowledge of pre- and post-processing of imaging data, including noise reduction, filtering, and mesh generation. (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). 10%
• C7. Knowledge of languages. Proficiency (level C2 CEFR scales) in French and/or English is highly valued for communication with international collaborators (demonstrated by official certificate in non-native English speakers. demonstrated by official certificate in non-native English speakers). 5%
• C8. Experience in a clinical or research environment (Experience will be assessed as a whole on the basis of the time/specialty ratio). 5%
• C9. Underrepresentation of gender by category, in accordance with Action S1 of the 2021-2024 Equality Plan, POSITIVE ACTION IN CALLS FOR POSTS. 5%
• C10. Interview. 20%