Data Scientist for Predictive Cardiovascular Medicine
4 weken geleden
Job Description
Project Overview
The time delay between medically relevant innovations and their establishment in medical practice is significant. Reducing this lag is a constant challenge for the health care system. Already today, a large amount of data is generated and stored daily in routine clinical practice and research. If we succeed in integrating and evaluating this comprehensive digital documentation of medical data, this promises a far-reaching gain in knowledge for medical science as well as an immediate benefit for those affected or at risk in the future.
New technologies make it possible to link routine clinical parameters with the human genome, the activity of human genes in tissue (transcriptome and proteome), or metabolites in the bloodstream (metabolome) in functional networks. The interpretation of these data requires a reference to diseased as well as phenotypically healthy persons, whereby knowledge is used from clinical and epidemiological studies, from health insurance companies, and finally from the individual (real world data, e.g., on diet, exercise, self-perception).
From a comprehensive digital view of medical and medically relevant data (Big Data), a new understanding of the development and treatment options of diseases will emerge when the data is appropriately combined and evaluated. The use of digital data and the storage of process parameters in routine clinical practice represent major and central challenges in modern medicine. Parallel to this, an innovative interpretation of coordinated changes in these parameters in the human organism as a whole, is important in order to better understand disease development or progression.
Project Goals
- Analyze large database (more than 100,000 individual cardiac catheterizations), angiograms, genetic analyses, and comprehensive clinical databases with standardized laboratory values, ECG and echocardiography data, using data analysis and data clustering, machine learning, unsupervised learning, etc.
- Detect key events in real-time during PCI treatment: angiogram, balloon inflation, stent deployment.
- In angiograms: automatically detect left and right tree, automatically label vessels, detect stenosis.
- For detected stenosis in angiograms: auto-determine best frame, delineate, quantify, identify calcified plaque.
- For angiograms from multiple angles: quantify and compare model to intra-vascular data (IVUS, OCT).
- Develop feature vectors describing relevant attributes extracted from raw data sequences (images, ECG, oxygen, etc).
- Develop machine learning algorithms to extract these feature vectors from unstructured real-time interventional data (e.g. image sequences).
- Develop algorithms for real-time lookup in the clustered ontology database.
Requirements and Responsibilities
As a Senior Researcher in Cardiovascular Data Analysis at TU Eindhoven, you will work on developing machine learning algorithms to extract feature vectors from unstructured real-time interventional data and develop algorithms for real-time lookup in the clustered ontology database. You will also analyze large database (more than 100,000 individual cardiac catheterizations), angiograms, genetic analyses, and comprehensive clinical databases with standardized laboratory values, ECG and echocardiography data, using data analysis and data clustering, machine learning, unsupervised learning, etc.
You will work in close collaboration with our team of experts in cardiovascular medicine, data analysis, and machine learning to develop innovative solutions for predictive cardiovascular medicine.
What We Offer
We offer a full-time employment for four years, with an intermediate evaluation (go/no-go) after nine months. You will spend 10% of your employment on teaching tasks. Salary and benefits (such as a pension scheme, paid pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labour Agreement for Dutch Universities, scale P (min. €2,872 max. €3,670). A year-end bonus of 8.3% and annual vacation pay of 8%. High-quality training programs and other support to grow into a self-aware, autonomous scientific researcher.
We are an internationally top-ranking university in the Netherlands that combines scientific curiosity with a hands-on attitude. Our spirit of collaboration translates into an open culture and a top-five position in collaborating with advanced industries.
How to Apply
If you are interested in working in an exciting, dynamic, high-tech environment, where you will contribute to creating the society of the future, then apply through the button on this page and upload an extended curriculum vitae including a detailed curriculum vitae, a letter of motivation, a portfolio with copies of diplomas with course grades and contact information of two references.
About Us
Eindhoven University of Technology is an internationally top-ranking university in the Netherlands that combines scientific curiosity with a hands-on attitude. Our spirit of collaboration translates into an open culture and a top-five position in collaborating with advanced industries.
Fundamental knowledge enables us to design solutions for the highly complex problems of today and tomorrow.
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