Human society faces big challenges, and generates knowledge
and new possibilities at an incredible pace. We are in the age
of “big data”, but also in the age of the sixth extinction.
However, without basic knowledge we will not be able to
successfully address these challenges. We believe that the current lack of predictive power we see in
the mathematical models we use in the field of ecology stems
from our inability to correctly identify the dynamic structure
of the system. The central goal of this research project is to
show across different examples that uncovering the underlying
dynamic structure of the system improves our ability to make
The postdoc we are looking for should be motivated to work
across different systems using tools from mathematics,
statistical physics, and computer science. Some questions we
would like to address assume a given interaction structure,
derive its theoretical predictions, and then develop solid
statistical methods to compare these predictions to data, at
least qualitatively. Other questions present a set of equally
plausible alternative hypotheses and then we are meant to
develop a computational methodological framework to compare
alternative hypotheses and conduct model selection in relation
to the always limiting data at hand. In particular, our
project uses examples from consumer-resource eco-evolutionary
theory, metacommunity theory, dynamics of disease propagation,
and random matrix theory mostly in the context of generalized
Lotka-Volterra systems. We look for an open-minded postdoc in
the field of physics, computer science or mathematical biology
with some background in any of these topics.
The candidate will be involved in parameterizing and running
simulations, using machine learning techniques, optimization
algorithms and big-data analysis methods. Potential candidates
should have a very strong background in R language, experience
in solving differential and difference equation models, and
knowledge in C, or a similar low-level programming language.
Experience with IBMs and random matrix theory will be
valuable. The candidate will work at the Center for Advanced
Studies in Blanes (a nice city in the northern coast of
Catalonia) as well as at Technical University of Madrid.
Although CSIC is a public institution, with little room to
negotiate the final terms of a salary, we still have some room
for negotiation depending on the career stage of the potential
candidate. In any case, it will fit well to the cost of living
in Blanes (e.g., apartment rental is about 400-750€/month).
If you are interested, please send us your CV, and we will
contact you back for a personal virtual interview. This search
will start in December 2022 until the position is filled.
Tentative starting date: Spring/Summer 2023 at the latest.