PhD Fellow in Data-Driven Mathematical Modelling of Ecohydrological Systems (m/f)

University of Luxembourg
Luxembourg
Position Type: 
Scholarship
Organization Type: 
University/Academia/Research/Think tank
Experience Level: 
Not Specified
Degree Required: 
Advanced Degree (Master's or JD)

EXPIRED

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The University of Luxembourg (UL) invites applications for a DRIVEN PhD Fellow (Doctoral Candidate) position (m/f) as part of the DRIVEN Doctoral Training Unit (https://driven.uni.lu), consisting of 19 doctoral candidates. DRIVEN is funded by the FNR PRIDE funding instrument https://www.fnr.lu/funding-instruments/pride/.

PhD Fellow in Data-Driven Mathematical Modelling of Ecohydrological Systems (m/f)

  • Réf: 50013528 - PRIDE PhD Fellow Ref: DRIVEN-PHD03.
  • Fixed-term 14-months initial contract, extendable to 48 months.
  • Full time (40 hours / week).
  • Employee and student status.
  • Enrollment in the DRIVEN Doctoral Training School.
  • Starting date: 01/10/2019.

Your Role

Research Direction:

This fully-funded position has significant scope for the candidate to shape their own research directions around the topic of data-driven mathematical modelling in ecohydrological systems. The broader context of the project is to improve modelling of plant ecosystems in order to make improved predictions in the context of rapidly changing environments (urbanisation, global warming and natural ecological processes).

Possible research directions for the candidate include, but are not limited to:

  • Bayesian model comparison to quantify the effects of physical laws, calibration, extremum principles and information theoretic approaches on eco-hydrological model precision and reliability.
  • Novel extremum principles for optimal nutrient uptake based on stochastic cost measures.
  • Uncertainty quantification of root plant nutrient uptake using mixed-dimensional coupled stochastic partial differential equation models.

The PhD candidate will have access to comprehensive experimental data on water-plant ecosystems from the Luxembourg Institute of Science and Technology (LIST).

The candidate will work with and contribute to leading open-source computational modelling tools, e.g. Stan (https://stanmc.org), pymc3 (https://docs.pymc.io/), pymatern, FEniCS Project (https://fenicsproject.org) and Renku (https://github.com/SwissDataScienceCenter/renku).

Supervision:

Your lead supervisor will be Jack S. Hale (University of Luxembourg, PDEs, Numerical methods, Continuum Modelling, Computational Sciences). Further supervision will be provided by Stan Schymanski (Luxembourg Institute of Science and Technology, Experimental and Conceptual Modelling in Ecohydrology, optimality principles) and Christophe Ley (University of Ghent, Bayesian Statistics, Applied Probability).

Framework:

You will be working as part of DRIVEN Doctoral Training Unit (DTU) funded by the FNR PRIDE scheme. The Computational and Data DRIVEN Science DTU will train a cohort of 19 Doctoral Candidates who will develop data-driven modelling approaches common to a number of applications strategic to the Luxembourgish Research Area and Luxembourg’s Smart Specialisation Strategies. DRIVEN will build a bridge between state-of-the-art data driven modelling approaches and particular application domains, including Computational Physics and Engineering Sciences, Computational Biology and Life Sciences, and Computational Behavioural and Social Sciences.

Your Profile

  • Masters degree in e.g. Applied Mathematics, Statistics, Engineering, Geophysics, Computational Sciences, Physics or other highly numerate and/or computational background.
  • A willingness to engage with ideas across Applied Mathematics, Statistics and Computational Sciences to advance the state of the art modelling strategies in Ecohydrology.
  • Excellent English language skills.
  • Willingness to work in an intercultural and international environment.
  • Ability to work independently and as part of a team.
  • Curiosity and self-motivation.

We offer

  • A dynamic and well-equipped research environment within Dr. Jack S. Hale’s team.
  • Intensive training in scientific and transferable skills, participation in schools. conferences and workshops.
  • Enrollment as a PhD student in the DRIVEN Training Unit, within an appropriate the UL doctoral school, e.g. Doctoral School of Science and Engineering.
  • Personal work space at UL.

Further Information

Job description:

Your primary tasks as a DRIVEN fellow are to:

  • Manage and drive forward your research project.
  • Attend doctoral school courses, trainings and social events.
  • Write scientific articles and your PhD thesis.
  • Disseminate your research at conferences and seminars.

No or minimal teaching duties are foreseen, except if the candidate desires it for career development purposes.

Gender policy:

UL strives to increase the proportion of female PhD students in its faculties. Therefore, we explicitly encourage women to apply.

Application submission:

Before proceeding with the submission of your application, please prepare the following documents.

  • Curriculum vitae (maximum two pages).
  • Motivation letter (maximum two pages) detailing how you meet the selection criteria for the given research direction.
  • Publication list (if any) and PDFs of those publications.
  • Master’s thesis (final or draft, if draft, then state the expected submission date).
  • Full contact details of two persons willing to act as referees.
  • Copies of diplomas, transcripts with grades, with English, French or German translation.

All documents should be uploaded in PDF format via the online submission system (no applications via email, please).

Selection process:

Candidates will be shortlisted based on the criteria detailed above. Shortlisted candidates will be invited for an interview and/or interviewed by phone.

Research work in Luxembourg:

Please see the Foreign Researcher’s Guide to Luxembourg for more information on research employment in Luxembourg and the procedures that apply.