DTIC-PLCT-2024-56 - Specialist support technician: Specialist in machine learning & medical image analysis and processing

Description

Project description: SimOSpine is an innovative digital health technology to prevent mechanical complications in corrective spine surgeries (CSS), the prevalence of which has largely increased in adults with spine deformities in the last five years. SimOSpine offers quantitative biomechanical assessments of the risk of mechanical failure while avoiding common barriers to patient-specific biomechanical modeling.

Main research field: Computational spine biomechanics & machine learning.

Tasks to be performed:

Research package 1: Disease-specific modeling

• Leverage pre-trained models: Adapt, train, and fine-tune existing models for 3D reconstruction tasks.

• Innovation: Design novel deep learning architectures and techniques to enhance 3D reconstruction performance.

• Data management: Collect and annotate relevant datasets for model training and evaluation.

• Pipeline development: Create efficient data pre-processing, post-processing, and inference pipelines to optimize model execution.

• Performance optimization: Optimize test-time and inference pipelines for speed and memory efficiency.

• Quality assurance: Implement robust validation processes to ensure the accuracy and reliability of the inference pipeline.

Group and complement: Group 3 Level U

Dedication and working hours: Full time (35h/week).

Planned remuneration approx: 28.676,14 € gross per year

Financing fund: Project PREUR02822 - HEu-ERC-CoG-O-Health-101044828-J.Noailly, “Scalable systems modeling to simulate body-level interplays among non-communicable diseases”, project that ends on 31/10/2027.

This position is funded by the EUROPEAN UNION, Program Horizon Europe (2021-2027).

Qualifications

Requirements: 

• High school-FP2.

The expected start date is November 25th 2024, the job is in Barcelona.

Selection criteria: The selection of the candidates will be made through evaluation of the curriculum and, where appropriate, with the carrying out a test and/or interview. Valuation will be as follows:

• Academic Training (0-50 points).

• Biomedical engineering degree or similar completed. Master’s degree and/or PhD in 3D Deep Learning and Medical Imaging (spine, intervertebral discs, ligaments…) will be highly valued.

• Performance in the required studies.

• Other professional training and experience, adequacy to the proposed profile (0-40 points):

• Master’s degree in biomedical image processing, computer science or similar.

• PhD in biomechanics.

• Additional training and/or experience in the artificial intelligence domain (i.e machine learning, deep learning,…) and/or data science.

• Additional training and/or experience in musculoskeletal (i.e. thoracolumbar spine) image segmentation , processing and analysis (X-Ray, CT, MRI…).

• Demonstrable hands-on experience in the research domain (adult spine surgery).

• Additional relevant skills (field-specific): demonstrated, e.g., through previous projects, and or through previous participation in contests, training, …

• Proficient in English

• Other merits (0-10 points):

• Candidates must have excellent teamwork and communication skills. 

• Good written and oral communication skills in English.

• Statement of purpose: experience, motivation for applying to this position, background fit, contribution of the position to the candidate’s future careers plans, …

The minimum score to pass the selection process is 70 points. The candidate with the highest score in the selection process will be offered the job.

Application Instructions

BASIC INFORMATION ON DATA PROTECTION: 

Data Controller: Universitat Pompeu Fabra

Purpose: Research support staff recruitment.

Rights: You can access your data; request their rectification, deletion and portability; you may object to their processing and request their limitation.

Additional information: Further detailed information is available on the website: https://www.upf.edu/web/personal/proteccio-de-dades-pas1

Equal Employment Opportunity Statement

UPF promotes a diverse and inclusive environment and welcomes applicants regardless of age, disability, gender, nationality, race, religion or sexual orientation.