Doctoral student in Computational Science with focus on expert elicitation and Bayesian modelling Full-time NEW

Doctoral Student In Computational Science With Focus On Expert Elicitation And Bayesian Modelling

Lund University was founded in 1666 and is repeatedly ranked among the world's top universities. The University has around 46,000 students and 8,500 staff based in Lund, Helsingborg and Malmö. We are united in our efforts to understand, explain and improve our world and the human condition.

Research and education at the Department of Earth and Environmental Sciences (MGeo) addresses fundamental and applied questions on the Earth's past, present and future climate and environment, including people's interactions with the natural world and consequences for human wellbeing. MGeo advances and deploys cutting-edge methods, models and technologies in environmental science, quaternary sciences, bedrock geology, paleontology, physical geography, biodiversity and ecosystem science, remote sensing, Geographic Information Science (GIS), and computational science for health and environment, to study processes spanning from the microscopic to the planetary, across all time scales.

As a doctoral student, you will be trained in a scientific approach. In short, you will be trained to think critically and analytically, to solve problems independently using the right methods, and to develop an awareness of research ethics. In addition, you will have the opportunity to work on projects, to develop your leadership and pedagogical skills. Throughout your studies, you will be guided by supervisors. Doctoral studies end with a thesis and a doctoral degree.

Computational Science is research that develops and applies advanced computational methods to answer research problems. A PhD project is interdisciplinary in the sense that both the scientific questions within the application and the computational aspects form a significant part of the thesis. This PhD project involves methodological development of probabilistic expert elicitation supporting Bayesian calibration of assessment models and characterisation of uncertainty in conclusions, with applications on environmental and human risk assessments. The PhD student will be part of a research project developing and testing of protocols for probabilistic expert elicitation in panel-based assessments.

Work duties

You will primarily devote yourself to your doctoral education, which mainly consists of writing a doctoral thesis. This PhD position is an opportunity to strengthen your knowledge and skills in statistical modelling, probabilistic uncertainty analysis, Bayesian thinking and in solving computational problems. You will together with researchers in the project, test elicitation methods on groups of diverse experts. We are therefore looking for someone with an interest in general scientific methodology and evidence evaluation. One of your tasks will be to develop software for eliciting and managing judgements from experts. You are expected to participate in the research project and to formulate your own research ideas on this topic. Participation in doctoral courses, seminars and international conferences are also expected.

In addition to studies, a maximum of 20% of working time may be spent on teaching and other departmental work. The PhD candidate is expected to be part of teaching in Bayesian modelling at undergraduate or graduate level, and will be given opportunity to contribute to trainings in expert knowledge elicitation to professionals outside academia.

Qualifications

To be eligible for admission and employment as a doctoral student, you must fulfil the requirements below.

A person meets the general admission requirements for third-cycle courses and study programmes if the applicant:

• has been awarded a second-cycle qualification, or
• has satisfied the requirements for courses comprising at least 240 credits of which at least 60 credits were awarded in the second cycle, or
• has acquired substantially equivalent knowledge in some other way in Sweden or abroad.

A person meets the specific admission requirements for third cycle studies in Computational Science if the applicant has:

• completed course requirements in a scientific or engineering subject area of at least 60 credits at basic or advanced level
• completed at least 30 credits in mathematics (advanced or basic level) and at least 7.5 credits in programming
• completed an independent work (e.g. degree project) in a relevant subject comprising at least 30 higher education credits.

The special qualification may also have been obtained through other equivalent education, which is assessed on a case-by-case basis. In order to enable interdisciplinary initiatives and significant in-depth studies in certain areas, qualifications other than the applicant's subject-specific competence in Computational Science may be taken into account.

Additional requirements

In order to complete the doctoral programme in question, the following are also required:

• knowledge in probability theory, statistical modelling and Bayesian inference (e.g. demonstrated by at least one course at advanced level)
• experience in programming and data analysis
• good ability to work independently and to formulate and tackle research problems.
• good written and oral communication skills
• good ability to cooperate
• very good knowledge of English, spoken and written

Selection criteria

The selection of eligible applicants will be made taking into account the ability to benefit from the training based on the following criteria:

• knowledge in expert elicitation, integration of expert knowledge in Bayesian modelling, decision analysis and probabilistic uncertainty analysis
• knowledge in R or Python
• experiences of risk assessment, systematic review and/or evidence synthesis; where applications to environmental, ecological or human endpoints are mertis
• high numerical skill and initiative-taking
• an original and personal suggestion for a research problem to carry out within the PhD position demonstrating an interest in the research topic

We offer

Lund University is a public authority which means that employees get particular benefits, generous annual leave and an advantageous occupational pension scheme.

About the employment

The employment is a fixed-term employment at full time, starting 2026-09-01 or as soon as possible after that.

Type of employment

The employment is a fixed-term employment at full time, starting 2026-09-01 or as soon as possible after that. Third cycle studies at LTH consist of full-time studies for 4 years. In the case of teaching and other departmental duties, the employment is extended accordingly. Doctoral studentships are regulated in the Higher Education Ordinance (1993:100), chapter 5, 1-7 §§.

Other

Candidates will be called for an interview that can be physical or made online.

How to apply

The application should be written in English and you must attach to your application:

• CV and personal letter with a justification of why you are interested in the PhD position and in what way it matches your interests and your educational background.
• Include a proposal of at maximum 1 page outlining a research problem you would like to tackle within the PhD project.
• Copies of issued study certificates and/or diplomas. These should prove your basic and special eligibility for the doctoral education subject and show that you have the subject knowledge required for the doctoral education project.
• Contact information for two to three references, actual letters of recommendation are not needed at this stage.

We welcome your application.