PhD-position in theoretical/computational ecology and evolutionary biology at Lund University

Project description
The fact that climate change can cause extinction of species is established, but our ability to study and quantify causality of such effects is challenging. Reliable predictions about future extinctions are thus also elusive. The aim of this project is to develop theory and quantitative methods that can improve our understanding and prediction of ecological and evolutionary processes that structures and maintains biological communities. The Ph.D. student should thus have basic knowledge of how ecological interactions, evolutionary processes, and dispersal of organisms in a variable environment can affect the structure and dynamics of communities. A particular focus will be on the phylogenetic difference between communities (phylobetadiversity), a metric of community structure that contains signals of both ecological, evolutionary and biogeographical processes. The student will formulate general theory of the causal link between process and phylobetadiversity through analysis of spatially explicit eco-evolutionary models. Theory will also be tested against empirical patterns through parametrization and validation of the models, given available data. There will be a particular focus on hummingbird community data from the Andes, which is a global biodiversity hotspot. By fitting models to hummingbird data, we aim to quantify the processes that have structured this unique ecosystem, and possibly predict how this system may respond to future conditions.

The project is at its start-up phase and part of the start-up of Dr. Mikael Pontarp’s research group at Lund University. The student will thus have the opportunity to contribute to the profile of the project as well as the direction it may take. To be able to utilize such an opportunity the student needs to be independent and persistent. In addition, to succeed in a theoretical and quantitative project like this, the student needs experience in and interest of differential equation models, agent-based simulations, evolutionary analysis, and statistics. The project is expected to be carried out in collaboration with Prof. Åke Brännström at Umeå Univeristy, Sweden who will serve as assistant supervisor.

Requirements and qualifications
The candidate should have a Masters degree in ecology/evolutionary biology. Alternatively, the candidate may have a degree in Physics, Mathematics or computer science. Knowledge of interacting ecological, evolutionary and biogeographical processes that underpin community structure and dynamics is desirable. Candidates also need to have proficiency, but not necessarily documented, in working with mathematical modeling, computation and computers and programming, e.g. in Matlab, Python, Julia, C++, etc. Knowledge of model parameterization and validation and Bayesian statistics is also desirable. Important qualities in a successful candidate are outgoing, curiosity, problem-solving, structured, independent and persistent.

Eligibility
Students with basic eligibility for third-cycle studies are those who- have completed a second-cycle degree- have completed courses of at least 240 credits, of which at least 60 credits are from second-cycle courses, or- have acquired largely equivalent knowledge in some other way, in Sweden or abroad.

The employment of doctoral students is regulated in the Swedish Code of Statues 1998: 80. Only those who are or have been admitted to PhD-studies may be appointed to doctoral studentships. When an appointment to a doctoral studentship is made, the ability of the student to benefit from PhD-studies shall primarily be taken into account. In addition to devoting themselves to their studies, those appointed to doctoral studentships may be required to work with educational tasks, research and administration, in accordance with specific regulations in the ordinance.

Application (deadline, 11 April)
Link English version: https://lu.varbi.com/en/what:job/jobID:258502/
Link Swedish version: https://lu.varbi.com/en/what:job/jobID:258502/

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