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PhD research topics

This page lists the currently available PhD projects to begin in 2022.

Applications needed to be submitted on or before 14 November 2021. By early January we will invite candidates for a presentation and interviews to be held on 14 and 15 February 2022. 

API staff may be contacted with questions about projects, but please do not email unsolicited application materials to API staff. More information about the recruitment process can be found here

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Pinpointing the lairs of Fast Radio Bursts (funding TBC)

Supervisor: Dr. Jason Hessels

Fast Radio Bursts (FRBs) are millisecond-duration radio flashes originating long-long ago in galaxies far-far away.  Their origin is one of the most compelling astrophysical mysteries of the past decade.  Whatever produces the FRBs must be capable of providing the necessary energy density and coherence conditions to produce radio flashes that can be observed from billions of lightyears distance.  The FRBs are thus fascinating probes of extreme astrophysics in action.  At the same time, the signal properties of FRBs are deformed as they pass through the intervening ionised material local to the source, in the intergalactic medium, and the interstellar medium of our own Milky Way.  Hence, FRBs are also unique probes of this intervening material and are likely to give us impactful cosmological insights.

 

Precise localisation is challenging but nonetheless key to understanding the origin of FRBs, and for using them as cosmological probes.  In this project we will use the European VLBI Network (EVN) to localise FRBs to their host galaxies and to study the detailed properties of the radio bursts themselves.  The EVN is a distributed network of radio telescopes spanning the globe; as we have previously demonstrated, we can use it to localise FRBs to a precision of a few milli-arcseconds.  This is sufficient to not only identify the host galaxy, but even the exact neighbourhood within the host.  We will also use these data to perform ultra-high time resolution studies of FRBs.  These observations will also be complemented by high-cadence single-dish observations and data from the Low-Frequency Array (LOFAR) as well.

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Inferring Black Hole and Neutron Star Properties with New Statistical and Machine Learning Methods

Supervisor: Dr. Daniela Huppenkothen

Black holes and neutron stars are at the heart of many open questions in both astrophysics and fundamental physics, for example in the study of strong gravity and the dense matter equation of state. Many of these sources, especially those that accrete matter from a companion star, exhibit a rich phenomenology of outbursts and of both spectral and temporal variations within those outbursts. The advent of modern X-ray telescopes like NuSTAR, NICER and—in the next few years—XRISM, eXTP and Athena, as well as the development of sophisticated numerical models, mean that we can ask ever more complex physical questions to be answered with these data sets and models. At the same time, our statistical methods have not kept pace, and the use of machine learning is still very rare in this field. 

The purpose of this project is to build state-of-the-art new statistical and machine learning methods to take full advantage of modern spectral-timing data sets. We will use simulation-based inference and neural networks to mitigate detector effects, and use these methods to help answer fundamental questions about black holes and neutron stars. Due to the interdisciplinary nature of the project, I welcome applications from candidates with any background relevant to the project, in any one of astronomy, physics, statistical modeling (regardless of field) or machine learning. Previous interdisciplinary experience in more than one of the above is not required and there will be ample learning opportunities across scientific disciplines as part of this project. This position is funded at the SRON Netherlands Institute for Space Research and will be a joint project. 

 

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Triple evolution towards transients

Supervisor: Dr. Silvia Toonen

Stellar mergers give rise to some of the most energetic events known in the universe; ranging from gravitational wave sources to electromagnetic transients (such as supernova type Ia and luminous red novae). Upcoming surveys such as aLIGO/Virgo and LSST will open unprecedented windows to these events, and directly provide information on their properties. However, the progenitors and their formation are often shrouded in mystery. In the past most of our efforts focused on modelling binary evolution, however, in the last few years our work demonstrated that a so far poorly explored part of the physics is very important; interaction of the binary with a third star. Our lack of a theoretical understanding of stellar triples leaves a major void in astronomy, and therefore a major opportunity! The aim of this project is to explore the evolution of triple systems, compute their properties and event rates using a computational approach, and finally set it against the results from gravitational wave and electromagnetic surveys to unravel the mysterious progenitors of stellar mergers.

To get a feeling about the kind of research you will be doing, here are a couple of papers by Dr. Toonen relevant to this project:

https://ui.adsabs.harvard.edu/abs/2021arXiv210804272T/abstract
https://ui.adsabs.harvard.edu/abs/2021ApJ...907L..19V/abstract
https://ui.adsabs.harvard.edu/abs/2020A%26A...640A..16T/abstract
https://ui.adsabs.harvard.edu/abs/2020A%26A...636A..31T/abstract
https://ui.adsabs.harvard.edu/abs/2017ApJ...841...77A/abstract