PhD Position: Numerical Analysis for Inverse Wave Scattering

We are looking for a PhD candidate with a background in numerical analysis to contribute to the development of numerical methods for inverse problems in wave propagation. You will become a member of the Department of Mathematics at Radboud University (Nijmegen, Netherlands), and join the research group of Laura Scarabosio, funded by the NWO Vidi programme ’Taming Frequency in Bayesian Inverse Wave Scattering’.

Inverse wave scattering involves reconstructing the properties of a spatial region from how it interacts with waves. It lies at the core of scientific discovery and technology, from radar to nanoscale metrology and geophysical exploration. The goal of the programme is to develop and rigorously analyse numerical methods for inverse problems in wave scattering within a Bayesian framework. Building on discretisation and solver techniques for time-harmonic wave propagation (governed by the Helmholtz equation) and sampling techniques (such as Monte Carlo methods), we aim to deliver computational tools capable of achieving high-resolution reconstructions and quantifying their reliability.

As a PhD candidate, you will contribute to the programme’s theme through the design, analysis and implementation of efficient numerical methods. You will also take part in light teaching duties (10%), participate in relevant conferences and workshops and publish your findings in peer-reviewed journals. The PhD position is funded for four years and will lead to a PhD degree from Radboud University upon successful completion.

Would you like to learn more about what it’s like to pursue a PhD at Radboud University? Visit the page about working as a PhD candidate.

PhD Position: Numerical Analysis for Inverse Wave Scattering

We are looking for a PhD candidate with a background in numerical analysis to contribute to the development of numerical methods for inverse problems in wave propagation. You will become a member of the Department of Mathematics at Radboud University (Nijmegen, Netherlands), and join the research group of Laura Scarabosio, funded by the NWO Vidi programme ’Taming Frequency in Bayesian Inverse Wave Scattering’.

Inverse wave scattering involves reconstructing the properties of a spatial region from how it interacts with waves. It lies at the core of scientific discovery and technology, from radar to nanoscale metrology and geophysical exploration. The goal of the programme is to develop and rigorously analyse numerical methods for inverse problems in wave scattering within a Bayesian framework. Building on discretisation and solver techniques for time-harmonic wave propagation (governed by the Helmholtz equation) and sampling techniques (such as Monte Carlo methods), we aim to deliver computational tools capable of achieving high-resolution reconstructions and quantifying their reliability.

As a PhD candidate, you will contribute to the programme’s theme through the design, analysis and implementation of efficient numerical methods. You will also take part in light teaching duties (10%), participate in relevant conferences and workshops and publish your findings in peer-reviewed journals. The PhD position is funded for four years and will lead to a PhD degree from Radboud University upon successful completion.

Would you like to learn more about what it’s like to pursue a PhD at Radboud University? Visit the page about working as a PhD candidate.

PhD Position: Numerical Analysis for Inverse Wave Scattering

We are looking for a PhD candidate with a background in numerical analysis to contribute to the development of numerical methods for inverse problems in wave propagation. You will become a member of the Department of Mathematics at Radboud University (Nijmegen, Netherlands), and join the research group of Laura Scarabosio, funded by the NWO Vidi programme ’Taming Frequency in Bayesian Inverse Wave Scattering’.

Inverse wave scattering involves reconstructing the properties of a spatial region from how it interacts with waves. It lies at the core of scientific discovery and technology, from radar to nanoscale metrology and geophysical exploration. The goal of the programme is to develop and rigorously analyse numerical methods for inverse problems in wave scattering within a Bayesian framework. Building on discretisation and solver techniques for time-harmonic wave propagation (governed by the Helmholtz equation) and sampling techniques (such as Monte Carlo methods), we aim to deliver computational tools capable of achieving high-resolution reconstructions and quantifying their reliability.

As a PhD candidate, you will contribute to the programme’s theme through the design, analysis and implementation of efficient numerical methods. You will also take part in light teaching duties (10%), participate in relevant conferences and workshops and publish your findings in peer-reviewed journals. The PhD position is funded for four years and will lead to a PhD degree from Radboud University upon successful completion.

Would you like to learn more about what it’s like to pursue a PhD at Radboud University? Visit the page about working as a PhD candidate.

Postdoc Position: Modelling Impacts of Agricultural Land Management Systems on Biodiversity

Organic and regenerative agricultural systems aim to reconcile agricultural production with the protection or restoration of biodiversity. However, the biodiversity benefits of these agricultural systems are not yet well understood. As a result, life cycle assessment (LCA) methodologies fall short in differentiating the biodiversity footprints of agricultural products originating from conventional and more nature-inclusive agricultural management systems.

The aims of this two-year postdoctoral project are:

1. To quantify and understand the effects of different agricultural management systems on biodiversity (such as impacts on species richness or species population sizes).
2. To develop and apply corresponding LCA characterisation factors able to distinguish biodiversity footprints of agricultural products originating from different systems and practices.

As a postdoctoral researcher in this project, you will first establish a database with measurements of biodiversity in agricultural and corresponding natural reference sites, to be collected from primary literature. Next, you will develop quantitative relationships describing how biodiversity responds to different agricultural land management systems. Third, you will develop LCA characterisation factors by integrating the biodiversity response estimates with maps of agricultural management systems in species-area models for different ecoregions. This will result in a set of LCA characterisation factors that enable quantifying the biodiversity footprints of agricultural products originating from different management systems. Finally, you will apply the new factors in a use case and document the findings in at least one scientific paper.

This project is a collaboration between Radboud University’s Department of Environmental Science and Unilever’s Safety, Environmental & Regulatory Science (SERS) group. As a postdoctoral researcher, you will be based at Radboud University, with regular meetings and exchanges with the Unilever team.

Postdoc Position: Modelling Impacts of Agricultural Land Management Systems on Biodiversity

Organic and regenerative agricultural systems aim to reconcile agricultural production with the protection or restoration of biodiversity. However, the biodiversity benefits of these agricultural systems are not yet well understood. As a result, life cycle assessment (LCA) methodologies fall short in differentiating the biodiversity footprints of agricultural products originating from conventional and more nature-inclusive agricultural management systems.

The aims of this two-year postdoctoral project are:

1. To quantify and understand the effects of different agricultural management systems on biodiversity (such as impacts on species richness or species population sizes).
2. To develop and apply corresponding LCA characterisation factors able to distinguish biodiversity footprints of agricultural products originating from different systems and practices.

As a postdoctoral researcher in this project, you will first establish a database with measurements of biodiversity in agricultural and corresponding natural reference sites, to be collected from primary literature. Next, you will develop quantitative relationships describing how biodiversity responds to different agricultural land management systems. Third, you will develop LCA characterisation factors by integrating the biodiversity response estimates with maps of agricultural management systems in species-area models for different ecoregions. This will result in a set of LCA characterisation factors that enable quantifying the biodiversity footprints of agricultural products originating from different management systems. Finally, you will apply the new factors in a use case and document the findings in at least one scientific paper.

This project is a collaboration between Radboud University’s Department of Environmental Science and Unilever’s Safety, Environmental & Regulatory Science (SERS) group. As a postdoctoral researcher, you will be based at Radboud University, with regular meetings and exchanges with the Unilever team.