The deadline for all calls are 1 May 2023 at 23:59 CET.
Supervisor: Corina-Gabriela Ciobotaru
The PhD student will carry out research within geometric group theory, as part of a Villum Young Investigator-funded project with a focus on limits of geometries over the p-adic numbers and will be supervised by Corina Ciobotaru.
The project will study geometric transitions of p-adic geometric structures, will combine techniques from metric geometry, Lie groups, Bruhat-Tits buildings, symmetric spaces, and will find applications to the representation theory of p-adic Lie groups.
Earliest starting date: 1 August 2023
Funding: Villum
In order to apply, and find more details, visit
Supervisor: Asger Hobolth
The purpose of this project is to develop an inference framework to model and analyse the mutational processes occurring in sperm cells.
The candidate will work on developing and applying machine learning methods to analyse data from testes and sperm samples. The relative weight of statistical modelling, methods development and data analysis will depend on the interests of the candidate
Most de novo mutations (>70%) originate from the father. We do not know why, when and how novel mutations arise during spermatogenesis, why older fathers pass on different types of mutations, and what influence the environment has. A significant proportion (>50%) of severe psychiatric diseases and male infertility cases are due to de novo mutations.
The analysis has been intractable due to the prohibitive costs of very deep sequencing data on different testis compartments. This has now changed, and in this project we develop new approaches to infer the mutational processes, and use this insight to make functional inference and prediction.
We are currently creating mutational sperm data from unique samples. We now wish to develop new mathematical and computational approaches inspired by cancer mutation modelling (non-negative matrix factorization) to understand the mutational processes occurring in sperm cells.
The final prediction model can directly aid clinical choices based on sequencing sperm alone. Non-invasive intervention to alleviate severe de novo disease can then become a reality.
The project is funded by the Novo Nordisk foundation as an interdisciplinary Data Science collaborative project between the Department of Growth and Reproduction at Copenhagen University Hospital (Kristian Almstrup), and Aarhus University with the Department of Mathematics (Asger Hobolth), the Department of Molecular Medicine (Søren Besenbacher) and the Bioinformatics Research Centre (Mikkel Heide Schierup & Thomas Bataillon).
Earliest starting date: 1 August 2023
Funding: Novo Nordisk Foundation
In order to apply, and find more details, visit
Supervisor: Asger Hobolth
Understanding the impact of global climate change and implementation of management resources for threatened populations requires detailed knowledge of the genetic and demographic history of these populations. Genetic polymorphism data represent a major resource of information, but the present methods are often limited to large spatial and temporal scales of limited practical interest.
In this project we develop new statistical methods to infer the recent and local evolutionary history of populations. We integrate temporal and spatial processes in an emerging matrix-analytical framework and apply the analysis tools to cutting-edge population genetic data from Occitania in France. Earlier this year we showed that full likelihood inference is feasible for population genetic data sets. A long-standing open problem in mathematical population genetics has been to calculate the likelihood for population genetic data sets under complex demographic models. We have now solved this problem, and want to further develop and apply the solution to improve statistical inference in population genetics.
The mathematical and statistical tools developed in this project can be used to obtain robust knowledge about the past and current demographic state of populations based on genomic data. The project facilitates improved understanding, monitoring and management of natural populations. Mathematical models for mutational patterns are also important for genetic diseases such as cancer or infertility.
The project is a joint effort between researchers from Aarhus University and researchers at the Centre de Biologie pour la Gestion des Populations in Montpellier.
Earliest starting date: 1 August 2023
Funding: Novo Nordisk Foundation
In order to apply, and find more details, visit
Supervisor: Cristiano Spotti
The PhD student will research within complex differential and algebraic geometry, as part of a Villum Young Investigator+ project.
The project focuses on the study of collapsing of canonical metrics (such as Einstein metrics) in complex geometry, aiming to explore the relations of such phenomena with algebraic and non-archimedean geometry. Such topics appear naturally in the study of moduli compactifications, and they have been also relevant in the geometric description of Mirror Symmetry (Kontsevich-Soibelman picture for the Strominger-Yau-Zaslow conjecture).
Earliest starting date: 1 August 2023
Funding: Villum
In order to apply, and find more details, visit
