Phd Position Multivariate Dependence Modelling and
5 maanden geleden
PhD Position Multivariate Dependence Modelling and Statistical Machine Learning Algorithms for Patient Risk Profiling-
Do you love exploring new ideas and want to positively impact healthcare by developing new mathematical methods? We're seeking a motivated person to join us as a PhD researcher in our group.
Job description
The project will be co-supervised by Özge Şahin and Tina Nane in Applied Probability from TU Delft and Annemieke Witteveen in Biomedical Signals and Systems from the University of Twente.
**Requirements**:
About You:
- Analytical Thinker: With a strong background in statistics, probability theory, and mathematics, you excel at analyzing complex datasets to derive meaningful insights.
- Tech-Savvy: You're comfortable navigating through datasets, especially in healthcare, using your technical skills. You are proficient in programming languages in R or Python.
- Collaborative Team Player: You engage with stakeholders across academia, healthcare, and industry, fostering inclusive partnerships to drive innovation in healthcare.
Conditions of employment
The TU Delft offers a customisable compensation package, discounts on health insurance, and a monthly work costs contribution. Flexible work schedules can be arranged.
For international applicants, TU Delft has the Coming to Delft Service. This service provides information for new international employees to help you prepare the relocation and to settle in the Netherlands. The Coming to Delft Service offers a Dual Career Programme for partners and they organise events to expand your (social) network.
TU Delft (Delft University of Technology)
Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context.
Challenge. Change. Impact
Faculty Electrical Engineering, Mathematics and Computer Science
The Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) brings together three scientific disciplines. Combined, they reinforce each other and are the driving force behind the technology we all use in our daily lives. Technology such as the electricity grid, which our faculty is helping to make completely sustainable and future-proof. At the same time, we are developing the chips and sensors of the future, whilst also setting the foundations for the software technologies to run on this new generation of equipment - which of course includes AI. Meanwhile we are pushing the limits of applied mathematics, for example mapping out disease processes using single cell data, and using mathematics to simulate gigantic ash plumes after a volcanic eruption. In other words: there is plenty of room at the faculty for ground-breaking research. We educate innovative engineers and have excellent labs and facilities that underline our strong international position. In total, more than 1000 employees and 4,000 students work and study in this innovative environment.
Click here to go to the website of the Faculty of Electrical Engineering, Mathematics and Computer Science.
Additional information
Application procedure
- Cover letter outlining your background and the motivation to pursue the PhD project (max. 1 page).
- A comprehesive Curriculum Vitae.
- Contact information of at least one academic referee.
- Transcripts and Master Degree / Diploma (if already available).
- Copy of Master thesis (or writing sample).
- A pre-employment screening can be part of the selection procedure.
- Please do not contact us for unsolicited services.
- FACULTY/DEPARTMENT***
**Faculty of Electrical Engineering, Mathematics & Computer Science**:
- JOB TYPE***
**PhD**:
- SCIENTIFIC FIELD***
**Engineering**:
- HOURS PER WEEK***
**36-40**:
- SALARY***
**€ 2.770,00 - € 3.539,00**:
- DESIRED LEVEL OF EDUCATION***
**University graduate**:
- VACANCY NUMBER***
**TUD05351**:
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