项目介绍

2024年10月4日

The MeBioS Biostatistics group at the KU Leuven is a young and dynamic team that focuses on the use of statistics and optimization in application areas ranging from the agrifood industry to the chemical and pharmaceutical industries. We perform fundamental and applied research in design of experiments, statistical model building, process monitoring, multivariate data analysis and chemometrics. We seek to strengthen our team with a PhD candidate who will focus on combinatorial constructions of modern experimental designs for efficient data collection in the context of product and process innovation.

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Project

Strategic data acquisition through efficient experimentation is key to rapid discovery and innovation in business and industry, as well as to product and process improvement. The field of experimental design, also referred to as Design of Experiments or DOE, provides the necessary tools to experiment efficiently. Traditional design of experiments textbooks distinguish between screening experiments and response surface experiments. The two-step approach to experimentation, in which a screening experiment is followed by a response surface experiment, has been successful for many decades. However, industries need to innovate at an ever increasing pace. The pressure to shorten the time to market is rising, and research and development has to be conducted more efficiently. One way to speed up the innovation phase despite the increasing complexity of modern products and processes is to combine screening and response surface experimentation in a single step. This requires new families of experimental plans, exploiting the technological advancements in modern laboratory equipment. Two attractive families of experimental plans are orthogonal minimally aliased response surface (OMARS) designs and orthogonal mixed-level (OML) designs. This project  focuses on combinatorial constructions of large OMARS designs and OML designs.

Profile

You hold a master degree (120 ECTS) in statistics, mathematics, physics, engineering, or a similar domain. Your master degree has been awarded by an institution of one of the countries of the EEA or Switzerland, or you have a NARIC certificate declaring the equivalence of your master degree. You have obtained this degree cum laude, magna cum laude or summa cum laude at most two years ago, and you have at most one year of research experience.
Your skills and interests include• statistical modelling• programming skills in, for instance, R and/or Python• fluency in English, spoken and written• autonomy, a sense of initiative and proactivity• knowledge of design of experiments is a plus

Offer

We offer a Ph.D. scholarship, initially for one year. After positive evaluation, the scholarship will be extended for three more years.

Interested?

For more information please contact Prof. dr. Peter Goos, tel.: +32 16 37 91 09, mail: peter.goos@kuleuven.be.You can apply for this job no later than November 04, 2024 via the online application tool

KU Leuven strives for an inclusive, respectful and socially safe environment. We embrace diversity among individuals and groups as an asset. Open dialogue and differences in perspective are essential for an ambitious research and educational environment. In our commitment to equal opportunity, we recognize the consequences of historical inequalities. We do not accept any form of discrimination based on, but not limited to, gender identity and expression, sexual orientation, age, ethnic or national background, skin colour, religious and philosophical diversity, neurodivergence, employment disability, health, or socioeconomic status. For questions about accessibility or support offered, we are happy to assist you at this email address.

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