We have a postdoc position at the Max Planck UCL Centre for Computational Psychiatry and Ageing Research and the Wellcome Centre for Human Neuroimaging to fill this summer. The eligible candidate should have a strong background in fMRI and decision making. They will join the developmental computational psychiatry group, working on innovative topics, such as structure learning, complex decision making and mental health. The focus will be on conducting fMRI research with the possibility to do computational modelling.

A Postdoc position is now available in the Dura-Bernal Lab at the State University of New York (SUNY) Downstate Health Sciences University (Brooklyn, New York), working on a new exciting multidisciplinary project entitled "Restoring motor function after spinal cord injury using multiscale modeling to decode neural latent dynamics from motor cortex EEG." The position is funded by New York State (NYS) Department of Health (DOH) Spinal Cord Injury Research program. The project aims to improve brain-machine interface decoders by combining multiscale modeling of motor cortex circuits, analysis of low-dimensional neural manifolds associated with behavior, and realistic simulation of EEG signals.

The lab of Dr. Kendrick Kay at the Center for Magnetic Resonance Research at the University of Minnesota is recruiting one or more postdocs. The lab seeks to integrate broad interdisciplinary insights to understand function in the visual system. One postdoc position is on a newly funded NIH R01 to develop, design, and collect a large-scale 7T fMRI dataset that samples a wide range of cognitive tasks on a common set of visual stimuli. The project is being conducted in close collaboration with co-PI Dr. Clayton Curtis (New York University). Activities in this grant include either (i) designing, collecting, and analyzing the large-scale neuroimaging dataset, (ii) technical work focused on extending and expanding the GLMsingle analysis method, and/or (iii) other related experimental or modeling work in visual/cognitive neuroscience. Another postdoc position is aimed towards integrating fMRI and intracranial EEG measurements during visual tasks (NSD-iEEG) and electrical stimulation. The general goal of this effort is to better understand signaling across the visual hierarchy (from early visual to higher order areas ventral temporal cortex and frontal/parietal areas). This project is in collaboration with PI Dr. Dora Hermes (Mayo Clinic).

The postdoc will work on a collaborative project between the labs of Yashar Ahmadian at the Computational and Biological Learning Lab (CBL), and Zoe Kourtzi at the Psychology Department, both at the University of Cambridge. The project investigates the computational principles and circuit mechanisms underlying human visual perceptual learning, particularly the role of adaptive changes in the balance of cortical excitation and inhibition resulting from perceptual learning. The postdoc will be based in CBL, with free access to the Kourtzi lab in the Psychology department.

The Research Training Group 2853 “Neuroexplicit Models of Language, Vision, and Action” is looking for 3 PhD students and 1 postdoc. Neuroexplicit models combine neural and human-interpretable (“explicit”) models in order to overcome the limitations that each model class has separately. They include neurosymbolic models, which combine neural and symbolic models, but also e.g. combinations of neural and physics-based models. In the RTG, we will improve the state of the art in natural language processing (“Language”), computer vision (“Vision”), and planning and reinforcement learning (“Action”) through the use of neuroexplicit models and investigate the cross-cutting design principles of effective neuroexplicit models (“Foundations”).

The lab of Christian Leibold invites applications of postdoc candidates on topics related to the geometry of neural manifolds. We will use spiking neural network simulations, analysis of massively parallel recordings, as well as techniques from differential geometry to understand the dynamics of the neural population code in the hippocampal formation in relation to complex cognitive behaviors. Our research group combines modelling of neural circuits with the development of machine learning techniques for data analysis. We strive for a diverse, interdisciplinary, and collaborative work environment.

The postdoc position is under the joint co-mentoring of Dr. Demian Battaglia and Dr. Romain Goutagny at the University of Strasbourg, France, in the Functional System's Dynamics team – FunSy. The position starts as soon as possible and can last up to two years. The job offer is funded by the French ANR 'HippoComp' project, which focuses on the complexity of hippocampal oscillations and the hypothesis that such complexity can serve as a computational resource. The team performs electrophysiological recordings in the hippocampus and cortex during spatial navigation and memory tasks in mice (wild type and mutant developing various neuropathologies) and have access to vast data through local and international cooperation. They use a large spectrum of computational tools ranging from time-series and network analyses, information theory, and machine-learning to multi-scale computational modeling.

The Institute for Neural Computation is looking for a postdoc in the field of Computational Neuroscience. The position is part of the group 'Theory of Neural Systems' and offers the opportunity to develop your own research profile and establish an independent research group. The research topic should be in the field of computational neuroscience on a system level, in particular modeling the visual system, episodic memory, or navigation in mammals. Collaborations with colleagues at the institute are welcome. The tasks include independent research projects and publications, acquiring third party funding, teaching, supervising student projects and your own PhD projects, and active participation in the local research environment.

1 Postdoc: Simulating & modelling neural dynamics involved in statistical/aversive learning and homeostatic/pain regulation with the scope to develop new projects. 1 Research Assistant: Conducting behavioral and neuroimaging experiments.

Postdoc position on Multi-objective Prediction Models for Machine Learning Applications.

A postdoc position is available under the shared supervision of Prof. Maxime Baud and Dr. Timothée Proix, who both specialize in quantitative neuroscience research. Together, they are running a three-year clinical trial involving patients with epilepsy who received a minimally invasive EEG device beneath the scalp for the chronic recording (months) of brain signals during wake and sleep. The postdoc will help with the analysis of massive amounts of EEG data, with a desire to build forecasting algorithms aiming at estimating the risk of seizures 24 hours in advance. The project lies at the interface between machine learning and EEG data analysis. The goal of the project is to develop machine learning algorithms to forecast seizures.

We are announcing one or more 2-year postdoc positions in identification and analysis of lexical semantic change using computational models applied to diachronic texts. Our languages change over time. As a consequence, words may look the same, but have different meanings at different points in time, a phenomenon called lexical semantic change (LSC). To facilitate interpretation, search, and analysis of old texts, we build computational methods for automatic detection and characterization of LSC from large amounts of text. Our outputs will be used by the lexicographic R&D unit that compiles the Swedish Academy dictionaries, as well as by researchers from the humanities and social sciences that include textual analysis as a central methodological component. The Change is Key! program and the Towards Computational Lexical Semantic Change Detection research project offer a vibrant research environment for this exciting and rapidly growing cutting-edge research field in NLP. There is a unique opportunity to contribute to the field of LSC, but also to humanities and social sciences through our active collaboration with international researchers in historical linguistics, analytical sociology, gender studies, conceptual history, and literary studies.

The postdoc position is focused on self-organized network modelling. The project aims to develop a theory of learning in liquid brains, focusing on how liquid brains learn and their adaptive potential when embodied as an agent interacting with a changing external environment. The goal is to extend the concept of liquid brains from a theoretical concept to a useful tool for the machine learning community. This could lead to more open-ended, self-improving systems, exploiting fluid reconfiguration of nodes as an adaptive dimension which is generally unexplored. This could also allow modes of learning that avoid catastrophic forgetting, as reconfigurations in the network are based on reversible movement patterns. This could have important implications for new paradigms like edge computing.

The Translational Social Neuroscience Unit at the Julius-Maximilians-Universität Würzburg (JMU) in Würzburg, Germany is offering a 2-year 100% postdoc position in social neuroscience. The unit studies the psychological and neurobiological processes underlying social interactions and decisions. Current studies investigate drivers of human social behavior such as empathy, social norms, group membership, and egoism, as well as the social modulation of anxiety and pain processing. The unit uses neuroscientific methods (functional magnetic resonance imaging, electroencephalography) and psychophysiological measures (heart rate, skin conductance), combined with experimental paradigms from cognitive and social psychology and simulations of social interactions in virtual reality. The unit also studies social interactions in everyday life using smartphone-based surveys and mobile physiological sensors. The position is initially limited until September 30, 2025 with the option for extension.

An NIH-funded collaboration between David Prober (Caltech), Thai Truong (USC) and Geoff Goodhill (Washington University in St Louis) aims to gain new insight into the neural circuits underlying sleep, through a combination of whole-brain neural recordings in zebrafish and theoretical/computational modeling. A postdoc position is available in the Goodhill lab to contribute to the modeling and computational analysis components. Using novel 2-photon imaging technologies Prober and Truong are recording from the entire larval zebrafish brain at single-neuron resolution continuously for long periods of time, examining neural circuit activity during normal day-night cycles and in response to genetic and pharmacological perturbations. The Goodhill lab is analyzing the resulting huge datasets using a variety of sophisticated computational approaches, and using these results to build new theoretical models that reveal how neural circuits interact to govern sleep.

Okinawa Institute of Science and Technology (OIST) has up to 10 open faculty positions in fields including life sciences and computational sciences. Each faculty member runs an independent research unit with internal funding including PhD students and postdoc/technical staff positions. A tenure-track faculty will have a tenure review within 6 years and a tenured faculty can renew research funding with reviews every 5 years till retirement at 70. OIST is an international, interdisciplinary graduate university without department boundaries. Education, research, and administration are run in English and no Japanese skills are required. A variety of supports for foreign researchers and family members are provided.

Claude Desplan is a Silver Professor of Biology and Neuroscience at NYU. He was born in Algeria and was trained at Ecole Normale Supérieure St. Cloud, France. He received his DSc at INSERM in Paris in 1983 and joined Pat O’Farrell at UCSF as a postdoc. There he demonstrated that the homeodomain, a conserved signature of many developmental genes, is a DNA binding motif. Currently, Dr. Desplan works at NYU where he investigates the generation of neural diversity using the Drosophila visual system.

Corticospinal neurons (CSN) are the cortical projection neurons that innervate the spinal cord and some brainstem targets with segmental precision to control voluntary movement of specific functional motor groups, limb sections, or individual digits, yet molecular regulation over CSN segmental target specificity is essentially unknown. CSN subpopulations exhibit striking axon targeting specificity from development into maturity: Evolutionarily newer rostrolateral CSN exclusively innervate bulbar-cervical targets (CSNBC-lat), while evolutionarily older caudomedial CSN (CSNmed) are more heterogeneous, with distinct subpopulations extending axons to either bulbar-cervical or thoraco-lumbar segments. The cervical cord, with its evolutionarily enhanced precision of forelimb movement, is innervated by multiple CSN subpopulations, suggesting inter-neuronal interactions in establishing corticospinal connectivity. I identify that Lumican, previously unrecognized in axon development, controls the specificity of cervical spinal cord innervation by CSN. Remarkably, Lumican, an extracellular matrix protein expressed by CSNBC-lat, non-cell-autonomously suppresses axon collateralization in the cervical cord by CSNmed. Intersectional viral labeling and mouse genetics further identify that Lumican controls axon collateralization by multiple subpopulations in caudomedial sensorimotor cortex. These results identify inter-axonal molecular crosstalk between CSN subpopulations as a novel mechanism controlling corticospinal connectivity and competitive specificity. Further, this mechanism has potential implications for evolutionary diversification of corticospinal circuitry with finer scale precision. "" Complementing this work, to comprehensively elucidate related axon projection mechanisms functioning at tips of growing CSN axons in vivo, I am currently applying experimental and analytic approaches recently developed in my postdoc lab (Poulopoulos*, Murphy*, Nature, 2019) to quantitatively and subcellularly “map” RNA and protein molecular machinery of subtype-specific growth cones, in parallel to their parent somata, isolated directly in vivo from developing subcerebral projection neurons (SCPN; the broader cortical output neuron population targeting both brainstem and spinal cord; includes CSN). I am investigating both normal development and GC-soma dysregulation with mutation of central CSN-SCPN transcriptional regulator Ctip2/Bcl11b.

This seminar is part of our “Emergent Scientists” series, an initiative that provides a platform for scientists at the critical PhD/postdoc transition period to share their work with a broad audience and network. Summary: These talks cover Alzheimer’s disease (AD) research in both mice and humans. Christiana will discuss in particular the translational aspects of applying mouse work to humans and the importance of timing in disease pathology and intervention (e.g. timing between AD biomarkers vs. symptom onset, timing of therapy, etc.). Siddharth will discuss a rare variant of Alzheimer’s disease called “Logopenic Progressive Aphasia”, which presents with temporo-parietal atrophy yet relative sparing of hippocampal circuitry. Siddharth will discuss how, despite the unusual anatomical basis underlying this AD variant, degeneration of the angular gyrus in the left inferior parietal lobule contributes to memory deficits similar to those of typical amnesic Alzheimer’s disease. Christiana’s abstract: Alzheimer’s disease (AD) is a debilitating neurodegenerative disorder that causes severe deterioration of memory, cognition, behavior, and the ability to perform daily activities. The disease is characterized by the accumulation of two proteins in fibrillar form; Amyloid-β forms fibrils that accumulate as extracellular plaques while tau fibrils form intracellular tangles. Here we aim to translate findings from a commonly used AD mouse model to AD patients. Here we initiate and chronically inhibit neuropathology in lateral entorhinal cortex (LEC) layer two neurons in an AD mouse model. This is achieved by over-expressing P301L tau virally and chronically activating hM4Di DREADDs intracranially using the ligand dechloroclozapine. Biomarkers in cerebrospinal fluid (CSF) is measured longitudinally in the model using microdialysis, and we use this same system to intracranially administer drugs aimed at halting AD-related neuropathology. The models are additionally tested in a novel contextual memory task. Preliminary findings indicate that viral injections of P301L tau into LEC layer two reveal direct projections between this region and the outer molecular layer of dentate gyrus and the rest of hippocampus. Additionally, phosphorylated tau co-localize with ‘starter cells’ and appear to spread from the injection site. Preliminary microdialysis results suggest that the concentrations of CSF amyloid-β and tau proteins mirror changes observed along the disease cascade in patients. The disease-modifying drugs appear to halt neuropathological development in this preclincial model. These findings will lead to a novel platform for translational AD research, linking the extensive research done in rodents to clinical applications. Siddharth’s abstract: A distributed brain network supports our ability to remember past events. The parietal cortex is a critical member of this network, yet, its exact contributions to episodic remembering remain unclear. Neurodegenerative syndromes affecting the posterior neocortex offer a unique opportunity to understand the importance and role of parietal regions to episodic memory. In this talk, I introduce and explore the rare neurodegenerative syndrome of Logopenic Progressive Aphasia (LPA), an aphasic variant of Alzheimer’s disease presenting with early, left-lateralized temporo-parietal atrophy, amidst relatively spared hippocampal integrity. I then discuss two key studies from my recent Ph.D. work showcasing pervasive episodic and autobiographical memory dysfunction in LPA, to a level comparable to typical, amnesic Alzheimer’s disease. Using multimodal neuroimaging, I demonstrate how degeneration of the angular gyrus in the left inferior parietal lobule, and its structural connections to the hippocampus, contribute to amnesic profiles in this syndrome. I finally evaluate these findings in the context of memory profiles in other posterior cortical neurodegenerative syndromes as well as recent theoretical models underscoring the importance of the parietal cortex in the integration and representation of episodic contextual information.