Sano PhD position: Computer-Aided System for Perinatal Care Based on Fetal Ultrasound using Deep Learning - Sano Centre for Computational Personalised Medicine

Sano PhD position

Project title: Computer-Aided System for Perinatal Care Based on Fetal Ultrasound using Deep Learning

Give us a chance to meet you

The Sano Centre for Computational Medicine is a new International Scientific Foundation located in Kraków, Poland. Sano aspires to be a major translational scientific institute, operating at the meeting point of academic science, established MedTech industry, and emerging start-up environment, combining the best of these three perspectives. Established with support from the European Commission and the Foundation for Polish Science, Sano aims to be a major driving force behind the advancement of computational medicine for the benefit of healthcare systems worldwide.

Sano will act as a core technology and expertise provider for industry, and creator of innovation, developing state-of-the-art solutions for healthcare. Thanks to the substantial funding and excellent European partnership network, Sano will bring a critical mass to this transformational field of research, in order to translate scientific advancements onto clinical practice. Sano’s ambition is to become the Reference Centre for Computational Medicine in Central Europe and build a reputation as a leading center on a global level.

As a cross-disciplinary institution, Sano will use machine learning/artificial intelligence (ML/AI), large scale computer simulations, data science, and other computational technologies towards overcoming global challenges in healthcare systems. The research agenda will be executed in close collaboration with Partners in Poland, EU and USA.

We value:

Passion – Passion in what we do, engagement in Sano operations, taking responsibility, providing initiative, being happy at work.
Innovation – Boldness in articulating and pursuing novel ideas, courage to think outside the box.
Integrity – Directness, openness, tolerance and respect. Scientific integrity (we do not cut corners).
Diversity – Diversity in backgrounds, cultures and opinions of Sano employees. Promotion of women in STEM.

Supervisors:

Warsaw University of Technology: Dr. Tomasz Trzciński (1^st supervisor)

Sano: Dr. Arkadiusz Sitek (2^nd supervisor)

Medical University of Warsaw: Dr. Michał Lipa (3^rd supervisor)

Project period: the project will start as soon as the candidate is accepted, and is planned for 4 years starting April/May 2021

Degree Awarding Institution: Warsaw University of Technology

Fetal ultrasound is an imaging technique that uses sound waves to produce images of a fetus in the uterus. This is a standard examination during pregnancy that can be used for the fetus growth monitoring, development and monitoring pregnancy. There are two main types of fetal ultrasound exams: transvaginal (mainly for cervix length measurement in case of preterm birth prediction) and transabdominal ultrasound (for fetal body part measurement in case of fetus growth monitoring). However, medical expertise and sonographic experience are required to find the proper measuring plane and acquire accurate measurements of the fetus and cervix.

Current diagnostics based on analysis of the ultrasound data is based on visual inspection of images by a gynecologist. In this study, we would like to develop a computer-aided system for perinatal care based on fetal ultrasound images using convolutional deep neural networks.

The system will guide gynecologists in case of the fetal body parts measurement, like head, abdomen, femur or gestational age estimation on transabdominal ultrasound. Based on transvaginal ultrasound, the system will help gynecologists to predict spontaneous preterm birth.

This project will be developed in cooperation with machine learning scientists from Warsaw University of Technology and experienced sonographers from the Medical University of Warsaw.

Aims/objectives of the project:

Develop deep convolutional neural networks for transabdominal ultrasound images analysis based on data coming from patients in 12-40 week of gestation.
Develop deep convolutional neural networks for transvaginal ultrasound images analysis between the first and second trimester.
Develop supervised and unsupervised learning methods to find new physical biomarkers in transvaginal ultrasound images to predict spontaneous preterm birth.
Verify the effectiveness of convolutional neural networks (CNN) with respect to the medical doctors.

You are excpected to:

do original research in this field under the direction of the supervisor;
participate in the many seminars by internal and external speakers as well as journal clubs and group activities;
collaborate with other PhD candidates, postdoctoral researchers and other Sano employees.

As our successful candidate you should have:

Master’s degree (completed or near completion) or 1^st Class undergraduate Honours degree in a relevant discipline such as computer science, biomedical engineering etc.;
knowledge of machine learning methods, computer vision, programming skills (Python);
interest in pursuing applied research;
excellent written and oral English communication skills;
prior research experience in academia or industry is very welcome.

We offer a fixed term contract for 40 hours per week for the duration of 4 years. This will be supported by an educational plan that includes attendance of courses and (international) meetings. The contract will include opportunities to participate in teaching and supervision of undergraduate and master students.

The salary, depending on relevant experience before the beginning of the employment contract, will be up to 8000 PLN gross per month, based on a full-time contract (40 hours a week) for the duration of 4 years with private medical care and a sports card.

This PhD will be a collaboration between Sano and Warsaw University of Science and Technology (PW), which will be the degree awarding body. The student will be based in Poland, Krakow operating in conjunction with the Cyfronet supercomputing centre hosted by AGH. As a part of the programme, the PhD Student will spend up to 6 months abroad with one of the partnering institutions for training and research visits.

Sano offers excellent opportunities for study and development, an access to many international conferences on computational medicine and a possibility to grow in a scientific society.

If you feel that this job opportunity is the career that you are looking for, please apply immediately and give Sano a chance to meet you. Please, be informed that Sano will contact only with Candidates fulfilling the formal criteria.

Sano is an equal-opportunity employer. We prioritize diversity and are committed to creating an inclusive environment for everyone. We value a spirit of enquiry and perseverance, provide the space to keep asking questions, and promote a culture of curiosity and creativity.

Do you recognize yourself in the job profile? Then we look forward to receiving your application.

Applications in .pdf should include:

a cover letter;
a curriculum vitae;

During later stages, you’ll also be asked to provide:

copies of your degree certificates;
two reference contacts.