Research Associate
Research Associate
Dr. Yasmine El-Shamayleh
Columbia University’s Mortimer B. Zuckerman Mind Brain Behavior Institute (the Zuckerman Institute) brings together world-class researchers from varied scientific disciplines to explore aspects of mind and brain, through the exchange of ideas and active collaboration. The Zuckerman Institute’s home, the Jerome L. Greene Science Center is a state-of-the-art facility on Columbia’s Manhattanville campus. Situated in the heart of Manhattan in New York City, the Zuckerman Institute houses over 50 laboratories employing a broad range of interdisciplinary approaches to transform our understanding of the mind and brain. In this highly collaborative environment, experimental, computational, and theoretical labs work together to gain critical insights into how the brain develops, performs, endures and recovers. The El-Shamayleh lab within the Zuckerman Institute is seeking a Staff Associate I to study the neural basis of vision. The Staff Associate I will assist in conducting behavioral and neurophysiological studies in large research mammals in a scientific wet-lab environment. The Staff Associate I will be responsible for the following: • Will assist in conducting wet-lab mammal training and the collection of behavioral and neural data. • Will assist in conducting behavioral and neurophysiological studies in research mammals. • Will assist the Principal Investigator in basic surgical procedures, in the daily care of large research mammals, experimental setup and will maintain lab supplies and reagents. Minimum Qualifications Bachelor’s degree in Neuroscience or Biological Sciences, required. At least one year of previous experience working in a wet lab; experience working with large mammals is highly desirable, as is knowledge of visual neuroscience and experience in performing basic surgical techniques. Qualified candidates must be capable of working independently on husbandry and training duties once instructed. Inquiries about this role should be directed to yasmine.shamayleh@columbia.edu and applications can be submitted to https://apply.interfolio.com/105441.
Faculty of Psychology
TU Dresden is one of eleven German Universities of Excellence. It provides an outstanding scientific infrastructure and ideal environment for interdisciplinary cooperation. The Faculty of Psychology offers a position as Research Associate (m/f/x) (subject to personal qualification employees are remunerated according to salary group E 13 TV-L) starting as soon as possible and limited until December 31, 2022 with the option of extension. The period of employment is governed by the Fixed Term Research Contracts Act (WissZeitVG). The position offers the chance to obtain further academic qualification and is funded by the Saxonian Ministry of Science, Culture, and Tourism (SMWK) and aimed at facilitating major funding initiatives at the TU Dresden. Tasks: The successful candidate will work together with the Faculty of Psychology in applying for major funding initiatives (e.g., Excellence Cluster) within the topics of psychology and neuroscience. The position will entail the following tasks: - preparation and editing of grant proposals including literature review, project descriptions, budget, and work plans - writing scientific publications such as reviews in close collaboration with an interdisciplinary team - research work in the field of psychology and cognitive neuroscience - scientific preparation of events such as workshops and conferences - writing executive summaries, high-level summaries, infographics, and other tools. For questions about the position please contact Prof. Dr. Katharina von Kriegstein (katharina.von_kriegstein@tu-dresden.de). The TU Dresden is an equal opportunities employer, committed to the advancement of individuals without regard to ethnicity, religion, gender, or disability. In case of equal suitability, people with severe disabilities or those with equivalence to the German Social Code IX (SGB IX) will be preferred for employment. Please submit your comprehensive application including a cover letter that briefly describes your personal qualifications and future career interests, CV, 1 to 2 publications, and contact details of two personal references by January 10, 2022 (stamped arrival date of the university central mail service applies), preferably via the TU Dresden SecureMail Portal https://securemail.tu-dresden.de by sending it as a single pdf document to julia.herdin@tu-dresden.de or by mail to: TU Dresden, Fakultät Psychologie, Institut für Allgemeine Psychologie, Biopsychologie und Methoden der Psychologie, Professur für Kognitive und Klinische Neurowissenschaft, Frau Prof. Dr. Katharina von Kriegstein, Helmholtzstr. 10, 01069 Dresden. Please submit copies only, as your application will not be returned to you. Expenses incurred in attending interviews cannot be reimbursed.
Dr Elliot J. Crowley
We have a position for a postdoctoral research associate to work on NAS and AutoML with Dr Elliot J. Crowley and the Bayesian and Neural Systems Group. The successful applicant will be based in the School of Engineering at the University of Edinburgh, and will have opportunities for collaboration within and outside of the school e.g. with colleagues in the Institute for Digital Communications and the Bayesian and Neural Systems Group. This position is funded for 24 months (provisional start date: November 2023) and the salary is UE07 £36,333 - £43,155 Per Annum.
Prof. Aline Villavicencio
The successful candidate will be expected to lead the design and development of strategies for more transparent machine learning models to generate accurate cross-lingual representations for idiomatic language, as well as to contribute to the design and development of resources and evaluation of downstream tasks, like machine translation. For both lines of research, you will build on state-of-the-art approaches based on deep learning.
Vassilis Vassiliades
We are looking for research associates in machine learning and robotics at the CYENS Centre of Excellence in Cyprus.
Shu-Chen Li
The Chair of Lifespan Developmental Neuroscience investigates neurocognitive mechanisms underlying perceptual, cognitive, and motivational development across the lifespan. The main themes of our research are neurofunctional mechanisms underlying lifespan development of memory, cognitive control, reward processing, decision making, and multisensory perception. We also pursue applied research to study effects of behavioral intervention, non-invasive brain stimulation, or digital technologies in enhancing functional plasticity for individuals of difference ages. We utilize a broad range of neurocognitive (e.g., EEG, fNIRs, fMRI, tDCS) and computational methods. The lab has several testing rooms and is equipped with multiple EEG (64-channel and 32-channel) and fNIRs systems, as well as eye-tracking and virtual-reality devices. The MRI scanner (3T) and TMS-device can be accessed through the university’s NeuroImaging Center. TUD is a university of excellence supported by the DFG, which offers outstanding research opportunities. Researchers in this chair are involved in large research consortium and cluster, such as the DFG SFB 940 „Volition and Cognitive Control“ and DFG EXC 2050 „Tactile Internet with Human-in-the-Loop“.
N/A
The Faculty of Engineering and Mathematics at Hochschule Bielefeld – University of Applied Sciences and Arts (HSBI) seeks to fill two positions as Research Associate in the field of Artificial Intelligence (AI) and Machine Learning (ML) within the framework of the research project 'FH-Kooperativ 2-2023: Cognitive Edge Computing for Multi-Sensor Applications with Sparse Data and High Latency Requirements' (Edge4SparseML), funded by the Federal Ministry of Education and Research. The research project's aim is to develop a method toolbox to efficiently run AI/ML procedures on resource-limited hardware for real-time applications. Based on the toolbox, it intends to investigate automated methods to explore the design space of suitable AI/hardware combinations in terms of a hardware/AI co-design. Particular emphasis lies on industrial applications with high latency requirements, considering both the complete chain as a linear process from modelling to inference and the repercussions of the choice of possible hardware configurations on the original modelling.
Decomposing motivation into value and salience
Humans and other animals approach reward and avoid punishment and pay attention to cues predicting these events. Such motivated behavior thus appears to be guided by value, which directs behavior towards or away from positively or negatively valenced outcomes. Moreover, it is facilitated by (top-down) salience, which enhances attention to behaviorally relevant learned cues predicting the occurrence of valenced outcomes. Using human neuroimaging, we recently separated value (ventral striatum, posterior ventromedial prefrontal cortex) from salience (anterior ventromedial cortex, occipital cortex) in the domain of liquid reward and punishment. Moreover, we investigated potential drivers of learned salience: the probability and uncertainty with which valenced and non-valenced outcomes occur. We find that the brain dissociates valenced from non-valenced probability and uncertainty, which indicates that reinforcement matters for the brain, in addition to information provided by probability and uncertainty alone, regardless of valence. Finally, we assessed learning signals (unsigned prediction errors) that may underpin the acquisition of salience. Particularly the insula appears to be central for this function, encoding a subjective salience prediction error, similarly at the time of positively and negatively valenced outcomes. However, it appears to employ domain-specific time constants, leading to stronger salience signals in the aversive than the appetitive domain at the time of cues. These findings explain why previous research associated the insula with both valence-independent salience processing and with preferential encoding of the aversive domain. More generally, the distinction of value and salience appears to provide a useful framework for capturing the neural basis of motivated behavior.
Trends in NeuroAI - SwiFT: Swin 4D fMRI Transformer
Trends in NeuroAI is a reading group hosted by the MedARC Neuroimaging & AI lab (https://medarc.ai/fmri). Title: SwiFT: Swin 4D fMRI Transformer Abstract: Modeling spatiotemporal brain dynamics from high-dimensional data, such as functional Magnetic Resonance Imaging (fMRI), is a formidable task in neuroscience. Existing approaches for fMRI analysis utilize hand-crafted features, but the process of feature extraction risks losing essential information in fMRI scans. To address this challenge, we present SwiFT (Swin 4D fMRI Transformer), a Swin Transformer architecture that can learn brain dynamics directly from fMRI volumes in a memory and computation-efficient manner. SwiFT achieves this by implementing a 4D window multi-head self-attention mechanism and absolute positional embeddings. We evaluate SwiFT using multiple large-scale resting-state fMRI datasets, including the Human Connectome Project (HCP), Adolescent Brain Cognitive Development (ABCD), and UK Biobank (UKB) datasets, to predict sex, age, and cognitive intelligence. Our experimental outcomes reveal that SwiFT consistently outperforms recent state-of-the-art models. Furthermore, by leveraging its end-to-end learning capability, we show that contrastive loss-based self-supervised pre-training of SwiFT can enhance performance on downstream tasks. Additionally, we employ an explainable AI method to identify the brain regions associated with sex classification. To our knowledge, SwiFT is the first Swin Transformer architecture to process dimensional spatiotemporal brain functional data in an end-to-end fashion. Our work holds substantial potential in facilitating scalable learning of functional brain imaging in neuroscience research by reducing the hurdles associated with applying Transformer models to high-dimensional fMRI. Speaker: Junbeom Kwon is a research associate working in Prof. Jiook Cha’s lab at Seoul National University. Paper link: https://arxiv.org/abs/2307.05916
Immunosuppression for Parkinson's disease - a new therapeutic strategy?
Caroline Williams-Gray is a Principal Research Associate in the Department of Clinical Neurosciences, University of Cambridge, and an honorary consultant neurologist specializing in Parkinson’s disease and movement disorders. She leads a translational research group investigating the clinical and biological heterogeneity of PD, with the ultimate goal of developing more targeted therapies for different Parkinson’s subtypes. Her recent work has focused on the theory that the immune system plays a significant role in mediating the heterogeneity of PD and its progression. Her lab is investigating this using blood and CSF -based immune markers, PET neuroimaging and neuropathology in stratified PD cohorts; and she is leading the first randomized controlled trial repurposing a peripheral immunosuppressive drug (azathioprine) to slow the progression of PD.
From the first spark to catching your breath: A love story in neuroscience
What are the things that draw us to a particular field of science and what is it that keeps us there? For Dr. Bahia, there was a particular attraction to sensory nerves; the monitors of the worlds inside and outside of our bodies. In this talk, Dr. Bahia will outline her career path as a neuroscientist resulting in the title of Research Associate. She will also talk about the longest project she has participated in, 'exploring the role of ion channels in sensory nerves' (rupress.org/jgp/article/147/6/451/43495/The-exceptionally-high-reactivity-of-Cys-621-is)