牛津大學(xué)（University of Oxford；勛銜：Oxon或Oxf），簡(jiǎn)稱“牛津”（Oxford），位于英國(guó)牛津，是一所公立研究型大學(xué)，采用傳統(tǒng)學(xué)院制。是羅素大學(xué)集團(tuán)成員，被譽(yù)為“金三角名校”和“G5”之一。牛津大學(xué)的具體建校時(shí)間已不可考，但有檔案明確記載的最早的授課時(shí)間為1096年，之后在1167年因得到了英國(guó)王室的大力支持而快速發(fā)展。

Postdoctoral Neuroscientist

University Of Oxford

Description

We are seeking to appoint a Postdoctoral Researcher to work as part of a team of scientists and clinicians investigating motor function and motivation in healthy people and patients with neurological conditions. You will join the MRC Brain Network Dynamics Unit (MRC BNDU; a division of the Nuffield Department of Clinical Neurosciences), which comprises an interdisciplinary collective of researchers with the collaborative goal of characterising the link between spatiotemporal brain network dynamics and behaviour. You will join a new research group led by Dr Ashwini Oswal (MD, PhD) and will be afforded rich integration and collaboration opportunities both within the BNDU and across the wider Nuffield Department of Clinical Neurosciences (NDCN). Within the NDCN we have particularly strong links with the Cognitive Neurology research group (led by Professor Masud Husain) and the Analysis group at the Oxford Centre for Human Brain Activity (led by Professor Mark Woolrich). National and international collaborations will also be fostered with centres including UCL and UCSF.

The overall purpose of this post is to conduct original research - using structural and functional brain imaging datasets - in support of a collaborative programme that aims to elucidate and develop novel therapies for brain network dysfunction in neurological conditions (e.g., Parkinson's disease). You will leverage converging methods including structural and functional brain imaging (e.g., MRI, EEG, MEG and LFP recordings), computational modelling, machine learning approaches and behavioural analysis. In addition to developing research protocols, you will play a key role in collecting, analysing, and reporting on high dimensional and multimodal datasets collected from healthy participants and patients.

The successful candidate will hold a Ph.D. or M.D. (theses to be submitted or already awarded) in a relevant area of research and have experience in computer programming languages (e.g., MATLAB, Python or R) for analysis of high dimensional or multimodal datasets. They will also have some prior knowledge or understanding of data collection and analysis techniques pertaining to neuroimaging, human neurophysiology, or cognitive neuroscience. Experience of conducting neuroimaging and/or electrophysiology, of working with open-source Machine Learning platforms and engaging in best practice supporting open science is desirable.

The post is fixed term for 3 years in the first instance.

Only applications received before 12:00 midday on 29th November 2022 will be considered.

Interviews will be held as soon as possible thereafter.

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