PhD in biostatistics: biodiversity monitoring with citizen-science data

As a PhD student, you conduct research in the field of biostatistics, more specifically ecological statistics. Your supervisor is Prof. Thomas Neyens, your co-supervisor is Dr. Maxime Fajgenblat. You are part of L-BioStat (Leuven Biostatistics Centre) at KU Leuven. Through Waarnemingen.be, more than 200,000 citizens in Flanders report observations of plants and animals. For most species these are the only data available, but they are not collected according to a fixed protocol, and not every species that is present is also seen. Our team has developed Bayesian models that account for this (site-occupancy models and joint species distribution models). In this PhD you will make these methods usable in practice, in collaboration with Natuurpunt Studie, which manages Waarnemingen.be. Examples of questions are:

• how can the models be made faster, so that they can be applied to thousands of species, and how much data do they need at a minimum;
• how can observations tell us not only where a species occurs, but also how abundant it is;
• how can reliable maps be made at the level of individual habitat patches, for example for wild bees in Flanders;
• to which locations should observers best be directed, so that new observations are as informative as possible?

You test and compare methods with simulation studies and real data, and translate the results into applications such as dashboards and reports for Natuurpunt. You work in Stan and R and also explore computing on graphics processors (GPUs). You publish your results in scientific journals, present your work at national and international conferences and build an (inter)national network.

• You hold a Master’s degree in (Bio-)Statistics or Data science (or equivalent) or Quantitative Biology; ecologists with a strong quantitative background are also encouraged to apply;
• You have excellent study results: you obtained your Master’s degree with at least distinction, or you stand out through strong scientific publications;
• You have a good command of English;
• You have strong communication skills, both written and oral, including with non-statisticians working for nature organisations and volunteers;
• You enjoy working in a multidisciplinary environment and you can work well in a team;
• Candidates with or without work experience will be considered. Experience with the research theme (through work or studies) is a plus;
• You can program in R (or Python/Julia); experience with Bayesian statistics (for example Stan);
• You are interested in ecology and biodiversity, and in putting research into practice;

• The position is funded by a research project. We expect you to apply for personal PhD funding (e.g. an FWO fellowship), with full support from the supervisory team.

• A full-time doctoral scholarship for 1 year, renewable after positive evaluation with 3 years, leading to a PhD after a total of 4 years;
• A research project with direct societal impact, in close collaboration with Natuurpunt Studie and with access to the data of Waarnemingen.be;
• Supervision by an experienced promoter within an international team of biostatisticians, as part of L-BioStat and I-BioStat;

• Training opportunities through the KU Leuven doctoral school, and the opportunity to present your work at national and international conferences, Research Field Agricultural sciences » Other Education Level Master Degree or equivalent Research Field Mathematics Education Level Master Degree or equivalent Research Field Biological sciences Education Level Master Degree or equivalent Languages ENGLISH Level Excellent Research Field Mathematics » Statistics Years of Research Experience None, * You hold a Master’s degree in (Bio-)Statistics or Data science (or equivalent) or Quantitative Biology; ecologists with a strong quantitative background are also encouraged to apply;

• You have excellent study results: you obtained your Master’s degree with at least distinction, or you stand out through strong scientific publications;
• You have a good command of English;
• You have strong communication skills, both written and oral, including with non-statisticians working for nature organisations and volunteers;
• You enjoy working in a multidisciplinary environment and you can work well in a team;
• Candidates with or without work experience will be considered. Experience with the research theme (through work or studies) is a plus;
• You can program in R (or Python/Julia); experience with Bayesian statistics (for example Stan);
• You are interested in ecology and biodiversity, and in putting research into practice;
• The position is funded by a research project. We expect you to apply for personal PhD funding (e.g. an FWO fellowship), with full support from the supervisory team.

• A full-time doctoral scholarship for 1 year, renewable after positive evaluation with 3 years, leading to a PhD after a total of 4 years;
• A research project with direct societal impact, in close collaboration with Natuurpunt Studie and with access to the data of Waarnemingen.be;
• Supervision by an experienced promoter within an international team of biostatisticians, as part of L-BioStat and I-BioStat;
• Training opportunities through the KU Leuven doctoral school, and the opportunity to present your work at national and international conferences;
• Access to computing infrastructure, including the Flemish Supercomputer Centre (VSC);
• A workplace in Leuven, one of the largest university cities in Europe, with an open and stimulating research environment;
• Preferred (but flexible) start date: 1 February 2027.