PhD position in AI‑powered 3DUltrasound for Early Prenatal Screening

Universitat Pompeu Fabra - Department / School of Engineering; Vitoria; Presencial; EUR 30.000 - 50.000; Jornada completa

Descripción de la vacante

A leading university in Spain is offering a fully funded doctoral researcher position focused on AI-based prenatal screening technology. Candidates will engage in high-level machine learning research, collaborating with experienced professionals, and gaining opportunities for publication and conference travel.

Servicios

Full tuition coverage

Access to doctoral training programs

Equipment and conference travel budget

Additional funding opportunities

Formación

• Master's (or equivalent) in Biomedical/Electrical Engineering, Computer Science, Physics, Applied Maths.
• Strong knowledge of Python and deep learning techniques.
• Experience with ultrasound or volumetric imaging is a plus.

Responsabilidades

• Drive core machine-learning research for the EmbryoScan project.
• Work on neural networks and 3D reconstruction techniques.
• Publish in top-tier venues and present at international conferences.

Conocimientos

Python

Deep learning

Educación

Master’s in Biomedical Engineering or related fields

Herramientas

PyTorch

TensorFlow

Descripción del empleo

Universitat Pompeu Fabra - Department / School of Engineering

Organisation / Company Universitat Pompeu Fabra - Department / School of Engineering Department Engineering Research Field Engineering » Biomedical engineering Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country Spain Application Deadline 15 Jun 2025 - 23 : 59 (Europe / Madrid) Type of Contract Temporary Job Status Full-time Offer Starting Date 13 May 2025 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No

Offer Description

EmbryoScan is an AI‑based platform that fuses multiple 2D ultrasound sweeps into high‑fidelity 3D volumes, with the ambition of optimizing routine fetal screening. Earlier, clearer imaging combined with automated segmentation and measurement promises faster, more accurate detection of congenital anomalies and a dramatic reduction in operator‑dependence.

• As the doctoral researcher, you will drive the core machine‑learning research that underpins EmbryoScan, working on :

Implicit‑representation neural networks and physics‑aware 3D reconstruction

• Automated plane finding & anatomy quantification
• Synthetic‑to‑real transfer learning and uncertainty estimation
• Close integration with clinical data from Vall d’Hebron Hospital for validation and deployment

You will publish in top‑tier venues, present at international conferences, and help translate the technology into clinical practice. This position is funded by a PIF1 / PRC fellowship offered by the Department of Engineering at Universitat Pompeu Fabra, which requires a teaching assistance load of 45 hours per academic year.

Your role

As the doctoral researcher, you will drive the core machine‑learning research that underpins EmbryoScan, working on :

• Implicit‑representation neural networks and physics‑aware 3D reconstruction
• Automated plane finding & anatomy quantification
• Synthetic‑to‑real transfer learning and uncertainty estimation
• Close integration with clinical data from Vall d’Hebron Hospital for validation and deployment

You will publish in top‑tier venues, present at international conferences, and help translate the technology into clinical practice.

• World‑class environment – Barcelona Center for New MedicalTechnologies (Department of Engineering, Universitat Pompeu Fabra) offers an ideal working environment, with a large critical mass of experienced senior investigators in diverse areas of biomedical engineering, junior postdoctoral researchers, and an international team of talented young PhD students.
• Interdisciplinary culture –embedded in the Barcelona Center for New MedicalTechnologies, you will collaborate daily with engineers, mathemat cians and clinicians.
• Direct mentoring from Prof.Gemma Piella (ICREA Academia awardee, DonaTIC Scientist of the Year 2022, and PI of 7 completed competitive r search projects; her group has graduated 14 PhDs to date) and from Dr. Alba Farràs (Maternal‑Fetal Medicine, Vall d’Hebron Hospital)
• Vibrant Barcelona life –a cosmopolitan city, English‑friendly graduate school, and travel budget for conferences and stays.

Supervision team

UPF is an equal‑opportunity institution. We actively welcome applications from all qualified candidates regardless of gender, disability, or background.

Join us and help reshape early prenatal screening through cutting‑edge AI!

Where to apply

E-mail

Requirements

Research Field Engineering Education Level PhD or equivalent

Skills / Qualifications

• Master’s (or equivalent) in Biomedical / Electrical Engineering, Computer Science, Physics, Applied Maths or related
• Strong Python & deep‑learning knowledge (including PyTorch or TensorFlow)

Additional Information

• Four‑year fully funded contract (salary + social security)
• Salary according to the UPF PIF1 / PRC scale, which is currently :

1470.98€ gross / month during the 1st and 2nd years

• 1576.05€ gross / month in the 3rd year
• 1970.06€ gross / month in the 4th year
• Full tuition fees, equipment and conference travel budget
• Additional funding opportunities – The group will actively support applications to competitive fellowships and participation in project‑based top‑ups to further increase remuneration.
• Access to UPF’s doctoral training programme & transferable‑skills courses

Eligibility criteria

Must‑haves

• Master’s (or equivalent) in Biomedical / Electrical Engineering, Computer Science, Physics, Applied Maths or related
• Strong Python & deep‑learning knowledge (including PyTorch or TensorFlow)

Nice-to-haves

• Experience with ultrasound or volumetric imaging
• Publications in medical‑image analysis / computer vision
• Knowledge of implicit neural representations, physics‑informed ML

Applications reviewed as they arrive.

Short‑listed candidates will be invited to a remote technical interview and to present a short research proposal.

Additional comments

Project and institution that finance the contract : This position is funded by a PIF1 / PRC fellowship offered by the Department of Engineering at Universitat Pompeu Fabra, which requires a teaching assistance load of 45 hours per academic year.

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