Machine self-learning from self-reported data using knowledge graphs

Sano Postdoc

Give us a chance to meet you

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.

Sano acts 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 institute on a global level.

As a cross-disciplinary institution, Sano uses machine learning/artificial intelligence (ML/AI), large scale computer simulations (HPC), 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.

Project title: Machine self-learning from self-reported data using knowledge graphs
Closing date: 16.04.2023
Level of education: PhD
Hours: 40 hours per week
Salary indication: up to 14000 PLN gross monthly
Project period: until the end of 2023 (possible extension)
Supervisor: Sano: Dr. Jose Sousa (Research Group Leader)

Humans’ behaviour is at the centre of the capability of Personal Health Data Science to impact evidence-based outcomes with self-reported data as a fundamental asset for that evidence. However, its use within machine learning processes is challenging, because self-reported data is noisy, volatile, and diverse while actual machine learning algorithms need clean, classified, and homogenous data, preferably in a silo, and within a single dimension approach.

The challenge for machine learning is then to be able to use self-reported data to allow a better understanding of individual health in a process from population to the individual. To use this data, we will focus on developing machine self-learning algorithms that overcome the human need to classify data and to build this we are going to start from knowledge graphs produced using machine self-learning capable to describe diseases, such as diabetes, obesity, dementia, or aged related macular degeneration (AMD) and aim for the development of a machine self-learning approach to support personalized decision making.

This would allow the development of policies and frameworks fitted to change behavior which is a central element to reduce the burden of these diseases on the health care systems. With this project we will develop the machine self-learning algorithms to create personal evidence on individual multiple long-term conditions (MLTC) also known as multimorbidity’s.

This project will be carried out in cooperation with machine learning and AI scientists at SANO and its partners and by developing external collaborations with Krakow health providers and with UK and Portuguese Universities.

You are expected to:

do original research under the direction of one of Research Group Leaders;
publish your work in peer-review journals and present during national and international conferences;
co-mentor junior scientists – PhD students and MSc students.

Required background and skills of the candidate:

recent (no more than 5 years) PhD in relevant field, preferably computer science;
at least one first-author research publication in a peer-reviewed scientific journal, top conference or currently in press (e.g. Neuroimage, Nature Methods, Nature Communications, Nature Scientific Reports, PloS, IEEE TMI, …);
excellent written and oral English communication skills;
knowledge of machine learning and deep learning methods;
knowledge of cloud technologies as desirable;
knowledge of big data frameworks such as Hadoop or Spark as desirable;
excellent programming skills – Python and/or R;
knowledge of SQL with NoSql as desirable.

We offer a fixed term contract for 40 hours per week until the end of 2023. 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 14000 PLN gross per month, based on a full-time contract (40 hours a week) with private medical care and a sports card. Contract extension after 12.2023 is possible and a subject of a future arrangement.

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;

Sano Postdoc