Dynamical up-scaling of flow in karst networks

Organisation/Company IFP Energies nouvelles (IFPEN) Research Field Geosciences » Hydrology Mathematics » Computational mathematics Physics » Computational physics Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country France Final date to receive applications 31 Aug 2026 - 00:00 (Europe/Paris) Type of Contract Temporary Job Status Full-time Hours Per Week 35 Offer Starting Date 2 Nov 2026 Is the job funded through the EU Research Framework Programme?

Horizon Europe - ERC Reference Number  Is the Job related to staff position within a Research Infrastructure? No

This project is part of the European ERC Synergy project Karst (Use the "Apply for this Job" box below). , which aims to develop a predictive flow model for an entire karst network. We will simulate water flows, possibly marked with tracers, in networks comprising millions of nodes. The flows will not necessarily be saturated, and nonlinear flow-rate/ / D p relationships between the inlet and outlet of the conduits will lead to the resolution of a large system of nonlinear equations.

A first thesis project currently underway focuses on simplifying these large systems of discretized Laplacian-type equations, assuming the network is static at a given time t, by grouping the unknowns and managing the uncertainty due to the conductivity of the conduits. Solutions have been developed and are available in Python packages.

This second doctoral student will focus on dynamic aspects when, due to external forces, the network of conduits changes topology as a result of competition between the system's recharge and drainage mechanisms. Reference simulations will be available following developments carried out by the Barcelona partner (openkarst code  ) using data acquired in the field (Swiss partner).

In a final phase, the karst network will be dynamically evolved by modeling changes in the network's geometry related to its drainage or filling due to external weather hazards, which can lead to major reorganizations of flows. Setting up monitoring techniques capable to anticipate such majors changes on the flow structure will be studied.

Real-world case studies from the ERC project or similar projects (K3, GEEAUDE) will be conducted. In a final phase, we will focus on speleogenesis, i.e., the emergence of karst structures due to fluid-rock interactions, a typical case of self-organization.

E-mail benoit.noetinger

Research Field Geosciences » Hydrology Education Level Master Degree or equivalent

Research Field Mathematics » Applied mathematics Education Level Master Degree or equivalent

Research Field Physics » Computational physics Education Level Master Degree or equivalent

Skills/Qualifications

That project will need good applied math and statistical physics skills added to network theory background

General IT skills (Python C++ etc ) will be appreciated

Specific Requirements

The project will involve travels on the Karst project partner location Barcelona, Neuchatel, Ljubjana)