Postdoctoral / Research Fellow position in complex network analysis: Critical events detection Postdoctoral or Research Fellow position is available to join the Complex Networks and Brain Dynamics group for the project: “Modelling and analysis of complex systems for safety of critical infrastructures“ as part of the National Center of Competence – Cybernetics and Artificial Intelligence funded by the Technology Agency of the Czech Republic, and related projects. The project involves developing, implementing, optimizing and applying techniques for detection and prediction of critical events and regime transitions and their propagation in complex networks, with applications in societally important real-world systems such as social and communication networks, computer networks and large-scale industrial systems. Conditions: • Initial contract is for 6 months duration (with possible extension up to 30 months based on project progress). • Positions are available immediately with starting date upon agreement. • Applications will be reviewed on a rolling basis with a first cut-off point on 30. 9. 2022. • This is a full-time fixed term contract appointment. Part time contract negotiable. • Monthly gross salary: 45 000 - 54 000 CZK based on qualifications and experience. Cost Of Living Comparison • Bonuses depending on performance and travel funding for conferences and research stays. • No teaching duties.

Postdoctoral / Junior Scientist position in Complex Networks and Information Theory A Postdoc or Junior Scientist position is available to join the Complex Networks and Brain Dynamics group for the project: “Network modelling of complex systems: from correlation graphs to information hypergraphs“ funded by the Czech Science Foundation. The project involves developing, optimizing and applying techniques for modelling complex dynamical systems beyond the currently available methods of complex network analysis and game theory. The project is carried out in collaboration with the Artificial Intelligence Center of the Czech Technical University. Conditions: • Contract is of 18 months duration (with the possibility of follow-up tenure-track application). • Starting date: position is available immediately. • Applications will be reviewed on a rolling basis with a first cut-off point on 30. 9. 2022. • This is a full-time fixed term contract appointment. Part time contract negotiable. • Monthly gross salary: 42 000 - 48 000 CZK based on qualifications and experience. Cost Of Living Comparison • Bonuses depending on performance and travel funding for conferences and research stays. • Contribution for reallocation costs for succesful applicant coming from abroad: 10 000 CZK plus 10 000 CZK for family (spouse and/or children). • No teaching duties

Research Fellow / Postdoc positions in Complex Networks and Brain Dynamics We are looking for new team members to join the Complex Networks and Brain Dynamics group to work on its interdisciplinary projects. The group is part of the Department of Complex Systems, Institute of Computer Science of the Czech Academy of Sciences - based in Prague, Czech Republic, https://www.cs.cas.cz/. We focus on the development and application of methods of analysis and modelling of real-world complex networked systems, with particular interest in the structure and dynamics of human brain function. Our main research areas are neuroimaging data analysis (fMRI & EEG, iEEG, anatomical and diffusion MRI), brain dynamics modelling, causality and information flow inference, nonlinearity and nonstationarity, graph theory, machine learning and multivariate statistics; with applications in neuroscience, climate research, economics and general communication networks. More information about the group at http://cobra.cs.cas.cz/. Conditions: • Contract is for 6-24 months duration. • Positions are available immediately or upon agreement. • Applications will be reviewed on a rolling basis with a first cut-off point on 30. 09. 2022, until the positions are filled. • This is a full-time fixed term contract appointment. Part time contract negotiable. • Monthly gross salary: 42 000 – 55 000 CZK based on qualifications and experience. Cost Of Living Comparison • Bonuses and travel funding for conferences and research stays depending on performance. • No teaching duties.

A Postdoc or Junior Scientist position is available to join the Complex Networks and Brain Dynamics group for the project: “Predicting functional outcome in schizophrenia from multimodal neuroimaging and clinical data“ funded by the Czech Health Research Council. The project involves the development of tools to predict the functional outcome of schizophrenia from multimodal neuroimaging, clinical and cognitive measurements taken early after disease onset. To overcome limitations due to high dimensionality of data, we combine robust machine-learning tools, data-driven feature selection and theory-based brain network priors. The project is carried out in collaboration with the National Institute of Mental Health, using its unique large rich imaging, cognitive and biochemical data of early stage schizophrenia patients. Conditions: • Contract is of 12-30 months duration (with possibility of a follow-up tenure-track application). • Starting date: position is available immediately. • Applications will be reviewed on a rolling basis with a first cut-off point on 30. 9. 2022 • This is a full-time fixed term contract appointment. Part time contract negotiable. • Monthly gross salary: 42 000 – 48 000 CZK based on qualifications and experience. Cost Of Living Comparison • Bonuses depending on performance and travel funding for conferences and research stays. • Contribution for reallocation costs for succesful applicant coming from abroad: 10 000 CZK plus 10 000 CZK for family (spouse and/or children). • No teaching duties.

A postdoc or junior scientist position is available to join the Complex Networks and Brain Dynamics group for the project: “Predicting functional outcome in schizophrenia from multimodal neuroimaging and clinical data“ funded by the Czech Health Research Council. For more info see: https://www.cs.cas.cz/job-offer/postdoctoral-junior-scientist-position-Hlinka2-2022/en The project involves the development of tools to predict the functional outcome of schizophrenia from multimodal neuroimaging, clinical and cognitive measurements taken early after disease onset. To overcome limitations due to high dimensionality of data, we combine robust machine-learning tools, data-driven feature selection and theory-based brain network priors. The project is carried out in collaboration with the National Institute of Mental Health, using its unique large rich imaging, cognitive and biochemical data of early stage schizophrenia patients. Conditions: • Contract is of 12-30 months duration (with possibility of a follow-up tenure-track application). • Starting date: position is available immediately • Applications will be reviewed on a rolling basis with a first cut-off point on 30.6.2022 • This is a full-time fixed term contract appointment. Part time contract negotiable. • Monthly gross salary: 40000 - 47000 CZK based on qualifications and experience. • Bonuses depending on performance and travel funding for conferences and research stays. • Contribution for reallocation costs for succesful applicant coming from abroad: 10 000 CZK plus 10 000 CZK for family (spouse and/or children). • No teaching duties

CIRAD (UMR TETIS laboratory, Montpellier) is offering a PhD position on Analysis of complex networks derived from interaction graphs for landscape dynamics analysis. The details of the offer are attached and at this link: https://nubes.teledetection.fr/index.php/s/CLXwBSWNkRSBzYD

Several postdoctoral positions are available in the Complex Networks and Brain Dynamics group (COBRA) at the Institute of Computer Science, Prague (Czech Republic). These positions are part of a larger, interdisciplinary consortium project that has recently been awarded (OPJAK BRADY). The project topics include: Topic 1: Detailed biophysical modelling of neurotransmitter action (supervised by Pavel Sanda). Topic 2: Computationally efficient mean-field models of cortical microcircuits (supervised by Helmut Schmidt). Topic 3: Whole-brain dynamics with applications particularly to schizophrenia and Parkinson's disease (supervised by Gustavo Deco). Topic 4: Data-driven model inversion and personalized parameter identification (supervised by Nikola Jajcay). Topic 5: Modelling interventions into arousal dynamics (supervised by Jaroslav Hlinka). Other related topics may be considered based on their fit to the overall project.

The Institute for Complex Systems at the National Research Council in Florence (Italy) invites applications for a one year Postdoctoral Scholar in the fields of computational neuroscience, complex networks and nonlinear dynamics. The successful applicant is expected to work closely with a multidisciplinary research team led by Dr. Simona Olmi on problems related to neuroscience. Specific topics of interest include but are not limited to the investigation of biologically realistic large-scale brain activity, the emergence of coupling between neural oscillations in neural architectures, the derivation of neural mass models in presence of short-term synaptic plasticity and/or spike-frequency adaptation as well as applications on brain structural connectivity matrices. Successful candidates are expected to primarily conduct computational and data driven research taking advantage of our international network of experimental collaborators and/or clinical partners.

Which nodes in a brain network causally influence one another, and how do such interactions utilize the underlying structural connectivity? One of the fundamental goals of neuroscience is to pinpoint such causal relations. Conventionally, these relationships are established by manipulating a node while tracking changes in another node. A causal role is then assigned to the first node if this intervention led to a significant change in the state of the tracked node. In this presentation, I use a series of intuitive thought experiments to demonstrate the methodological shortcomings of the current ‘causation via manipulation’ framework. Namely, a node might causally influence another node, but how much and through which mechanistic interactions? Therefore, establishing a causal relationship, however reliable, does not provide the proper causal understanding of the system, because there often exists a wide range of causal influences that require to be adequately decomposed. To do so, I introduce a game-theoretical framework called Multi-perturbation Shapley value Analysis (MSA). Then, I present our work in which we employed MSA on an Echo State Network (ESN), quantified how much its nodes were influencing each other, and compared these measures with the underlying synaptic strength. We found that: 1. Even though the network itself was sparse, every node could causally influence other nodes. In this case, a mere elucidation of causal relationships did not provide any useful information. 2. Additionally, the full knowledge of the structural connectome did not provide a complete causal picture of the system either, since nodes frequently influenced each other indirectly, that is, via other intermediate nodes. Our results show that just elucidating causal contributions in complex networks such as the brain is not sufficient to draw mechanistic conclusions. Moreover, quantifying causal interactions requires a systematic and extensive manipulation framework. The framework put forward here benefits from employing neural network models, and in turn, provides explainability for them.