Applied Mathematics
Applied Mathematics
Kerstin Bunte
We offer a postdoctoral researcher position within the Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence at the University of Groningen, The Netherlands. The position is funded by an NWO Vidi project named “mechanistic machine learning: combining the explanatory power of dynamic models with the predictive power of machine learning“. Systems of Artificial Intelligence (AI) and Machine Learning (ML) gained a tremendous amount of interest in recent years, demonstrating great performance for a wide variety of tasks, but typically only if they are trained on huge amounts of data. Moreover, frequently no insight into the decision making is available or required. Experts desire to know how their data can inform them about the natural processes being measured. Therefore we develop transparent and interpretable model- and data-driven hybrid methods that are demonstrated for applications in medicine and engineering. As a postdoc, you will work together with Kerstin Bunte and her team within the Intelligent Systems group, as well as a network of interdisciplinary collaborators in the UK and Europe from various fields, such as Computer Science, Engineering and Applied Mathematics.
Lorenzo Fontolan
An ERC-funded postdoctoral position is available in the Cossart lab at the Mediterranean Institute of Neurobiology (INSERM, Aix-Marseille University, Marseille, France) to work in a collaborative, interdisciplinary, and friendly environment. The Cossart lab aims at understanding memory circuits in the brain and describing how they develop in health and disease. The candidate will apply their skills to extract information from our datasets, build computational models to make predictions, and work in close collaboration with experimentalists. The candidate will be co-supervised by Dr. Lorenzo Fontolan, a computational neuroscientist who recently started his research group at Inmed.
Boris Gutkin
A three-year post-doctoral position in theoretical neuroscience is open to explore the mechanisms of interaction between interoceptive cardiac and exteroceptive tactile inputs at the cortical level. We aim to develop and validate a computational model of cardiac and of a somatosensory cortical circuit dynamics in order to determine the conditions under which interactions between exteroceptive and interoceptive inputs occur and which underlying mechanism (e.g., phase-resetting, gating, phasic arousal,..) best explain experimental data. The postdoctoral fellow will be based at the Group for Neural Theory at LNC2, in Boris Gutkin’s team with strong interactions with Catherine Tallon-Baudry’s team. LNC2 is located in the center of Paris within the Cognitive Science Department at Ecole Normale Supérieure, with numerous opportunities to interact with the Paris scientific community at large, in a stimulating and supportive work environment. Group for Neural Theory provides a rich environment and local community for theoretical neuroscience. Lab life is in English, speaking French is not a requirement. Salary according to experience and French rules. Starting date is first semester 2024.
Joseph Lizier
The successful candidates will join a dynamic interdisciplinary collaboration between A/Prof Mac Shine (Brain and Mind Centre), A/Prof Joseph Lizier (School of Computer Science) and Dr Ben Fulcher (School of Physics), within the University's Centre for Complex Systems, focused on advancing our understanding of brain function and cognition using cutting-edge computational and neuroimaging techniques at the intersection of network neuroscience, dynamical systems and information theory. The positions are funded by a grant from the Australian Research Council 'Evaluating the Network Neuroscience of Human Cognition to Improve AI'.
Chloé Bourgeois-Antonini
The M.Sc. Mod4NeuCog is a two-year interdisciplinary master's program at Université Côte d’Azur (Nice, France), which aims to train active researchers at the crossroads of computer science, applied mathematics and cognitive neuroscience. Students will learn to model cognitive functions using mathematical and computational tools and will be specialized in computational neuro/cognitive science, able to work in fully interdisciplinary settings, with a strong foundation in mathematics.
Ahmed H. Qureshi
The Cognitive Robot Autonomy and Learning (CoRAL) Lab, led by Professor Ahmed Qureshi, has an immediate opening for a postdoctoral position focused on physics-informed methods for scaling deep reinforcement learning to complex dynamical systems. The position is initially open for one year and will be renewed annually based on performance. The candidate will have the opportunity to publish and present papers at top conferences such as RSS, ICRA, ICML, and NeurIPS and collaborate with an outstanding team of graduate and undergraduate students. The Cognitive Robot Autonomy and Learning (CoRAL) Lab is in the Department of Computer Science at Purdue University. The lab offers an excellent environment for exploring different aspects of robotics, from algorithm development to real-robot implementations.
Md Sahidullah
We are inviting applications from highly motivated and talented individuals for our fully-funded PhD programme at the Institute for Advancing Intelligence, TCG CREST. The PhD degree will be conferred by the Academy of Scientific and Innovative Research (AcSIR), an Institute of National Importance, which recently ranked 11th in the NIRF list. Under this PhD Programme, I am particularly looking for full-time PhD students to work in one of the following areas: Privacy and security in speech communication, Speech and audio analytics, Speech processing for healthcare applications. You can check other available research areas in https://www.tcgcrest.org/iai-admission-2025/
Tiago de Paula Peixoto
We’re hiring a post-doctoral researcher to join the Inverse Complexity Lab at IT:U, Linz, Austria. We are looking for an early-stage or more advanced postdoctoral scholar who is interested in building on our ongoing projects, or developing their own research agenda related to inverse problems in network science, complex systems modeling, and/or connections to machine learning. This position is not bound to a particular research project, and the successful applicant will enjoy intellectual independence and freedom to choose research topics. This position is guaranteed for 3 years. The gross salary range is € 66,532 to € 70,000 (corrected for inflation), depending on previous experience. The employment conditions in Austria include completely free health care (also for family members), social security benefits, 25 days per year of paid vacations, flexible working hours, and possibility of home office. In addition, IT:U will provide a KlimaTicket—a unified transport pass which gives free access to the entire transportation system in Austria, including trains and local public transport.
Lyle Muller
Postdoctoral and graduate research positions are available at Western University (London, ON) and the Fields Lab for Network Science (Toronto, ON). These positions will be supervised by Lyle Muller and involve collaborations with advanced methods of brain imaging (Mark Schnitzer, Stanford), neuroengineering (Duygu Kuzum, UCSD), theoretical neuroscience (Todd Coleman, Stanford), and neurophysiology of visual perception (John Reynolds, Salk Institute for Biological Studies). In collaboration with this multi-disciplinary team, researchers will bring together data science, computational science, and applied mathematics to understand spatiotemporal dynamics and computation in the circuits of neocortex. The project may include intermittent travel between labs to present results and facilitate collaborative work.
When and (maybe) why do high-dimensional neural networks produce low-dimensional dynamics?
There is an avalanche of new data on activity in neural networks and the biological brain, revealing the collective dynamics of vast numbers of neurons. In principle, these collective dynamics can be of almost arbitrarily high dimension, with many independent degrees of freedom — and this may reflect powerful capacities for general computing or information. In practice, neural datasets reveal a range of outcomes, including collective dynamics of much lower dimension — and this may reflect other desiderata for neural codes. For what networks does each case occur? We begin by exploring bottom-up mechanistic ideas that link tractable statistical properties of network connectivity with the dimension of the activity that they produce. We then cover “top-down” ideas that describe how features of connectivity and dynamics that impact dimension arise as networks learn to perform fundamental computational tasks.
The impact of elongation on transport in shear flow
I shall present two recent piece of work investigating how shape effects the transport of active particles in shear. Firstly we will consider the sedimentation of particles in 2D laminar flow fields of increasing complexity; and how insights from this can help explain why turbulence can enhance the sedimentation of negatively buoyant diatoms [1]. Secondly, we will consider the 3D transport of elongated active particles under the action of an aligning force (e.g. gyrotactic swimmers) in some simple flow fields; and will see how shape can influence the vertical distribution, for example changing the structure of thin layers [2]. [1] Enhanced sedimentation of elongated plankton in simple flows (2018). IMA Journal of Applied Mathematics W Clifton, RN Bearon, & MA Bees. [2] Elongation enhances migration through hydrodynamic shear (in Prep), RN Bearon & WM Durham.