Open positions

We’re hiring! New positions open to join the ICE team:

PhD position in glacial landscape modelling

Project Description: The landscape of the European Alps has been shaped from the combination of a number of processes, e.g., uplift, fluvial or glacial erosion. In particular, glacial erosion is known to be a major control on mountain height in (formerly) glaciated mountain ranges. Coupling the underlying model physical components over relevant time scales of  the Quaternary is challenging due to high computational costs of traditional physical modelling, especially those associated with the computation of the high order ice mechanics, which are essential to explain the formation of U-shaped valleys formed by glacial erosion. However, the arrival of GPU as new computational paradigm, machine learning emulated models, as well as modern implementation libraries (e.g. TensorFlow) are game changing to run landscape evolution models over very long time scales. Such a landscape evolution model would permit to lead novel modelling experiments and to test hypothesis on the long-term interaction between the climate and erosion that explain today’s Alpine landscape. This is precisely the goal of this PhD thesis, which includes both model development and application. The goal of the PhD thesis will be i) to undertake the Instructed Glacier Model (IGM, https://github.com/jouvetg/igm) – a newly introduced glacier model accelerated by deep-learning – and to include new physical components relevant for modelling landscape evolution ii) to apply the model over the European Alps. The research involves a large diversity of fields including glaciology, physical and numerical modelling of surface Earth processes, machine learning, climatology, and geomorphology. The successful candidate will join the ICE (https://wp.unil.ch/ice/) group in the Institute of Earth Surface Dynamics which specializes in paleoenvironment and landscape evolution in a range of different environmental settings.

Candidate Profile: The chosen candidate will have a master degree either in Earth sciences, geosciences, geophysics, geology, physics, applied mathematics, machine learning, computer sciences, or a related field, and should have a sharp interest in the modelling of geophysical or processes. Previous experience in numerical modelling, machine learning, and Python programming is an asset. Good writing and communication skills in English as well as the motivation to fruitfully collaborate within an interdisciplinary framework are essential.  Knowledge in French language is preferable but not necessary.

Job description: The majority of the workload will be dedicated to the completion of the Ph.D. thesis, which includes model development, modelling applications, and the writing of peer-reviewed publications. Participation in internal and international meetings and conferences is expected, as well as the active participation in the research institute. A component of the workload will consist in assisting with teaching and research duties: teaching activities under the supervision of a professor, research work not directly related to the personal PhD topic, technical and administrative tasks related to the activities of the Institute. Seeking to promote an equitable representation of men and women among its staff, the University of Lausanne encourages applications from women.

For more information, please contact Guillaume Jouvet (guillaume.jouvet@unil.ch).

The full job description and the application website (entitled “Graduate Assistant in modelling glacial landscape evolution (20685)” can be found here: https://career5.successfactors.eu/career?company=universitdP&career_job_req_id=20685&career_ns=job_listing&navBarLevel=JOB_SEARCH

Review of applications will start on 3 April 2023, and will continue until the position is filled. Flexible starting date.

PostDoc position in glacier modelling

In the framework of a newly-funded project entitled “Reconciling geological and modelled reconstructions of Alpine glacier evolution from the Last Glacial Maximum into the Holocene”, we are looking to fill  1 2-year PostDoc position at the University of Lausanne (UNIL, ICE group, https://wp.unil.ch/ice/).

Project summary: Quaternary glaciations have left numerous geological footprints in the landscape of the European Alps, especially during and after the Last Glacial Maximum (LGM). Despite extensive field evidence and dating constraints, the chronology of the glacier evolution is far from being well understood. Numerical models accounting for the glacier thermo-dynamics, climate and mass balance have proven to be promising tools for simulating ice extent evolution and fill knowledge gaps. However, existing models generally show significant biases with geomorphological reconstructions.  These discrepancies between field- and model-based reconstructions is in good part due to spatially too coarse models that do not resolve the complex relief of the Alps. Unfortunately, traditional ice flow models are computationally too expensive to achieve the resolution required over timescales of several tens of millennia. To overcome this bottleneck, the goal of this project is adopt a new modelling strategy using Instructed Glacier Model (IGM, github.com/jouvetg/igm) — a new glacier model accelerated by deep-learning. This project at the interface of glacier modelling and Quaternary geology aims i) to further develop IGM to include relevant physical processes (such as thermo-mechanics, sediment transportation, and moraine production …), ii) to integrate new geological records (such as trimlines, dated moraines sequences, erratic boulders, etc.). Ultimately this project aims to produce a well constrained high-resolution transient reconstruction of ice extent over the Alps and enhance our ability to interpret the palaeo record and our understanding of the spatio-temporal response of glaciers to climate variations from the LGM through the Holocene.

Role of the candidate:  The PostDoc (based at UNIL, working in strong collaboration with UZH) will be responsible for developing and setting up the model (developments and assimilation of field data).  The candidate is expected to have core expertise in numerical glacier modelling. Previous experience in Python programming, machine learning, and knowledge in Quaternary geology is an asset. Good writing and communication skills in English as well as the motivation to fruitfully collaborate with the research groups in Lausanne and Zurich and in an interdisciplinary framework are essential.

If you wish to apply, please send a cover letter, CV, and references within a single pdf file to Guillaume Jouvet (guillaume.jouvet@unil.ch). A first review of applications will start on 3 April 2023, and will continue until the position is filled. Flexible starting date.