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Neuroscience CV Example

A neuroscience CV highlights your research into the nervous system, brain function, and neurological processes using advanced experimental techniques.

Recommended template: Compact

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Key Skills to Include

ElectrophysiologyNeuroimagingBehavioural AnalysisHistologyStatistical AnalysisMATLABAnimal ModelsCognitive Testing

Quick Tips

  • Detail specific neuroscience techniques and model systems you have worked with.
  • Include publications, posters, and conference presentations in neuroscience.
  • Highlight experience with neuroimaging tools such as fMRI, EEG, or MEG.
  • Showcase interdisciplinary skills that bridge biology, psychology, and computation.

Ready to build your CV?

Start with the Compact template and customise it for your science role.

How to Write Your Neuroscience CV

A neuroscience CV should demonstrate your expertise in studying the nervous system through experimental, computational, or clinical approaches. Selection panels and hiring managers want to see evidence of technical mastery, publication output, and the ability to design experiments that advance understanding of brain function. Your CV should clearly present your research focus, the techniques you use, and the impact of your findings.

CV Structure

Use a reverse-chronological format with sections for your profile, research experience, education, publications, grants, and technical skills. Each role should describe the research group, funding source, and your specific project. Follow with publications and achievements. Include a separate publications section listing papers in reverse chronological order. Keep the CV to two to three pages.

CV Format

Select a clean academic template. Neuroscience hiring panels expect clear structure and easy navigation. Include your ORCID iD, Google Scholar link, and any open-source code repositories. Use consistent citation formatting and save as a PDF. Avoid decorative elements — substance matters more than style.

CV Profile Examples

Systems Neuroscientist

Systems neuroscientist with eight years of postdoctoral research experience investigating sensory processing and decision-making circuits using in vivo electrophysiology in rodent models. Proficient in multi-electrode array recordings, optogenetics, and computational modelling of neural dynamics using MATLAB and Python. Author of twelve peer-reviewed publications including two in Nature Neuroscience.

Cognitive Neuroscientist

Cognitive neuroscientist specialising in human memory and attention, with extensive experience in fMRI experimental design, EEG acquisition, and advanced multivariate pattern analysis. Six years of research experience across two Russell Group universities with a strong teaching record in undergraduate neuroscience and psychology modules. Wellcome Trust-funded researcher with nine publications.

Graduate Neuroscientist

Neuroscience PhD candidate in the final year of doctoral research investigating neuroinflammation in Alzheimer's disease using transgenic mouse models. Experienced in immunohistochemistry, confocal microscopy, behavioural testing, and quantitative image analysis. Seeking a postdoctoral position that combines preclinical neuroscience with translational approaches to neurodegenerative disease.

State your research focus, model system, core techniques, and headline metrics such as publication count or grant income. Mention the level at which you operate — from PhD student to principal investigator — to set expectations.

Key Skills for Your Neuroscience CV

Electrophysiology

Recording electrical activity from neurons using extracellular multi-electrode arrays, patch clamp, or EEG to study neural coding and circuit function.

Neuroimaging

Acquiring and analysing brain imaging data using fMRI, structural MRI, diffusion tensor imaging, PET, or EEG/MEG techniques.

Behavioural Analysis

Designing and quantifying animal and human behavioural tasks to measure cognitive, sensory, and motor function in experimental settings.

Histology

Processing and staining brain tissue sections for microscopic analysis using immunohistochemistry, fluorescence, and cresyl violet methods.

Statistical Analysis

Applying parametric, non-parametric, and Bayesian statistical methods to neural and behavioural datasets using MATLAB, R, or Python.

MATLAB

Writing custom analysis scripts and toolboxes for electrophysiology data processing, signal analysis, and computational modelling.

Animal Models

Working with rodent models of neurological disease and conducting surgical procedures, behavioural testing, and tissue collection under Home Office licence.

Cognitive Testing

Administering standardised neuropsychological assessments to measure memory, attention, executive function, and other cognitive domains.

Optogenetics

Using light-activated proteins to selectively activate or inhibit specific neural populations in vivo to establish causal relationships in brain circuits.

Work Experience Examples

Describe the scientific question, your experimental approach, the techniques used, and the outcomes. Include publications, conference presentations, and any methodological innovations. Mention supervision and teaching activities. Quantify your output — papers published, students supervised, grant income secured.

Postdoctoral Research Associate — Neuroscience

UCL Queen Square Institute of Neurology, London

Investigated cortical mechanisms of perceptual decision-making using electrophysiology and optogenetics in awake, behaving mice, funded by a Wellcome Trust Senior Investigator Award.

Responsibilities

  • Performed chronic multi-electrode implant surgeries and recorded from populations of neurons in visual and prefrontal cortex during decision-making tasks.
  • Designed and implemented behavioural paradigms using custom-built apparatus controlled by Arduino and Bpod systems.
  • Analysed electrophysiological data using MATLAB and Python, applying dimensionality reduction, decoding models, and drift-diffusion frameworks.
  • Led optogenetic manipulation experiments, injecting viral vectors and performing fibre-optic implant surgeries to selectively inhibit neural populations.
  • Supervised two PhD students and contributed to their project design, data analysis, and manuscript preparation.

Achievements

  • Published a first-author paper in Nature Neuroscience demonstrating a causal role for prefrontal cortex in perceptual confidence, cited over 150 times.
  • Secured a £35,000 travel and research grant from the Gatsby Charitable Foundation to support a three-month collaboration at a partner laboratory in the United States.
  • Developed an open-source MATLAB toolbox for neural decoding analysis that has been downloaded over 800 times from GitHub.

Research Assistant — Neuroscience

University of Cambridge, Department of Clinical Neurosciences

Supported clinical neuroscience research investigating biomarkers of traumatic brain injury using neuroimaging and cognitive testing in patient cohorts.

Responsibilities

  • Recruited and assessed patients with traumatic brain injury, administering standardised cognitive test batteries and quality-of-life questionnaires.
  • Coordinated MRI scanning sessions, including structural, diffusion tensor imaging, and resting-state fMRI acquisitions.
  • Preprocessed neuroimaging data using FSL and FreeSurfer, conducting volumetric and tractography analyses.
  • Managed the clinical research database, ensuring data accuracy and compliance with research ethics and data protection requirements.

Achievements

  • Contributed imaging analysis to a publication in Brain identifying white matter biomarkers predictive of long-term cognitive outcome after TBI.
  • Recruited 45 patients ahead of schedule for a multicentre clinical study, meeting the site target three months early.

Education & Qualifications

List your PhD with thesis title and supervisor. Follow with master's and bachelor's degrees. Include relevant prizes, funded studentships, or prestigious summer programmes. Mention any formal training in research methods, statistics, or ethics.

PhD in Neuroscience

Doctoral qualification demonstrating the ability to conduct independent neuroscience research and contribute original findings to the field.

Home Office Personal Licence (PIL)

Licence required for researchers conducting regulated procedures on animals under the Animals (Scientific Procedures) Act 1986.

FHEA

Fellowship of the Higher Education Academy demonstrating competence in university-level teaching and student support.

GCP Training

Good Clinical Practice certification required for neuroscientists involved in clinical research with human participants.

Frequently Asked Questions

What techniques should I highlight on a neuroscience CV?
Focus on the techniques most relevant to your target position. For systems neuroscience roles, highlight electrophysiology, optogenetics, and computational analysis. For cognitive neuroscience, emphasise neuroimaging methods and behavioural paradigms. For clinical roles, include patient assessment, GCP training, and neuroimaging analysis pipelines. Always be specific about the model systems and platforms you use.
How important are publications for neuroscience positions?
Publications are the primary currency of academic neuroscience. List them prominently and highlight first-author and high-impact journal papers. For industry positions, publications demonstrate scientific rigour but are weighed alongside practical skills and collaborative ability. Include preprints and conference proceedings as well as peer-reviewed articles.
Should I include my animal licence on my neuroscience CV?
Yes, if you hold a Home Office Personal Licence, include it. Many neuroscience positions require PIL holders, and stating this upfront saves time for both you and the employer. Mention the specific modules you are licensed for and any additional training such as surgical techniques or anaesthesia courses.
How long should a neuroscience CV be?
Two to three pages is typical. PhD students and early postdocs should aim for two pages. Established researchers with substantial publication lists, grant portfolios, and teaching records may extend to three or four pages. Focus on quality and relevance — every entry should demonstrate research capability, scientific impact, or professional development.

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