CV
layout: archive title: “CV” permalink: /cv/ author_profile: true —
Dr Natasha L. Taylor (PhD)
National University of Singapore
dr.natasha.l.taylor@gmail.com
Professional Summary
Neuroscientist with over 6 years of experience analyzing high-dimensional time-series datasets using Python, MATLAB and R. Expertise in statistical and predictive modelling, low-dimensional embeddings, feature extraction and signal processing of large multi-modal datasets. Proven record in developing automated analytical pipelines, predictive feature extraction with clinically validated outcomes and delivering reproducible insights. Seeking to apply advanced analytical expertise in an industry-partnered role for translatable impact.
Technical Skills
Programming Languages
Python, MATLAB, R, Bash
Data Science & Machine Learning
Machine learning, classification, regression, feature selection, dimensionality reduction
Statistical & Time-Series Analysis
Time-series analysis, signal processing, statistical modeling, correlation analysis, dynamic systems analysis, network analysis
Data Engineering & Workflow Tools
Git, Linux, HPC environments, automated pipeline development, reproducible workflows
Data Visualization
Scientific visualization, multidimensional data visualization
Professional Experience
Postdoctoral Research Fellow
National University of Singapore | 2025 – Present
- Developed statistical analysis pipelines to analyze high-dimensional multi-modal datasets
- Designed automated data processing workflows, improving efficiency and reproducibility for large timeseries datasets
Postdoctoral Research Associate
The University of Sydney | 2024 – 2025
- Built predictive models to identify biomarkers associated with clinical outcomes
- Collaborated with interdisciplinary teams including clinicians, engineers, and data scientists
- Designed computational models to analyze dynamic patterns in large-scale datasets
- Developed automated pipelines in Python and MATLAB for processing and analyzing high-dimensional data
- Applied statistical modeling and machine learning methods to identify predictive features
- Published findings in high-impact scientific journals
Lecturer/Tutor
The University of Sydney | 2019 – 2023
- Created content and learning outcomes for Masters of Brain & Mind Sciences
- Delivered senior lectures on use cases of neuroimaging applications in clinical diagnoses
Visiting Research Assistant
** University of Waterloo, Canada | 2023
PhD Researcher
The University of Sydney | 2019 – 2024
- Developed novel statistical approaches for analyzing complex time-series datasets
- Built automated pipelines to process large-scale neuroimaging datasets
- Applied predictive modeling to identify relationships between biological signals and clinical outcomes
- Published 15+ peer-reviewed research papers
Education
Doctor of Philosophy (Neuroscience)
Faculty of Medicine & Health, The University of Sydney | 2024
Bachelor of Medical Science (First Class Honours)
The University of Sydney | 2019
Selected Publications
Taylor, N.L., et al. (2026). Preoperative Cholinergic Signatures Drive Segregated Brain Architecture in Postoperative Delirium.
Taylor, N.L., et al. (2026). Dysfunctional Resting-state Network Connectivity predicts postoperative delirium after major surgery. British Journal of Anaesthesia.
https://doi.org/10.1016/j.bja.2025.11.036
Taylor, N.L., et al. (2024). Causal evidence for cholinergic stabilisation of attractor landscape dynamics. Cell Reports.
https://doi.org/10.1016/j.celrep.2024.114359
Taylor, N.L., et al. (2022). Structural and Functional Connectivity of Neuromodulatory Systems Underpins Dynamic Shifts in Brain Network Topology. NeuroImage.
https://doi.org/10.1016/j.neuroimage.2022.119455
Taylor, N. L., et al. (2022). The Contribution of Noradrenergic Activity to Anxiety-Induced Freezing of Gait. Movement Disorders.
https://doi.org/10.1002/mds.28999
Full publication list available upon request.
Awards
2024: Faculty of Medicine & Health EMCR Symposium Best Presentation, The University of Sydney. 2023: Emerging Aspirations Award from Centre for Complex Systems, The University of Sydney. 2023: James Kentley Memorial Funds Scholarship, $5,300, The University of Sydney. 2022: Nominee for The University of Sydney representative for CSL Florey Next Generation Award, $50,000. 2021: Research Training Program Stipend Scholarship, $35,950 (p.a.), The University of Sydney. 2020: Australian Government RTP Fees Offset Scholarship, The University of Sydney. 2019: Honours Physiology Scholarship, $8,000, The University of Sydney. 2019: ForeFront Prize for Best Presentation, $1,000, The University of Sydney.
Comunity Experience
- 2024 – Current: ECR Elect Representative Organisation for Human Brain Mapping Australia Chapter
- 2024 – Current: Social Committee Elect Student & Post-doc Organisation for Human Brain Mapping
- 2024 – Current: Women in Science Special Interest Group ECR Representative
- 2023 – Current: Member of Women in STEM Australia
- 2022 – Current: Member of Neuroscience Theme, School of Medical Sciences, University of Sydney
- 2022 – Current: Member of Organization of Computational Neuroscience
- 2021 – Current: Member of Australasian Cognitive Neuroscience Society
- 2021 – Current: Member of Dementia Australia Research Foundation
- 2020- Current: ECR Representative Organisation for Human Brain Mapping- Australia
- 2020 – Current: Member in Sydney Neuroscience & Complexity group
- 2020 – Current: Volunteer within the Cure Brain Cancer Australia
Links
GitHub: https://github.com/NatashaLTaylor
Website: https://natashaltaylor.github.io/