Jordan McIvor
Post-Doctoral Researcher
Highest degree :
Post-Doctoral
Field of study :
Computational Biophysics
Location :
London
Citizenships :
New Zealander
Experience :
5 Year(s)
Countries :
Italy, New Zealand
Gender :
Female
Sectors :
chemistry
Data science
Data analysis
Biochemistry
PhD-trained computational biophysicist and data scientist specialising in data-driven exploration of complex biological systems, with extensive experience in molecular simulations, advanced sampling, and quantitative analysis. Proficient in Python and Bash, using statistical modeling, clustering, and machine learning pipelines to extract insights from high-dimensional, noisy datasets. Experienced in automating workflows, visualising complex data, and translating computational results into biological and mechanistic insights. Demonstrated ability to communicate findings to interdisciplinary teams, contribute to drug discovery projects, and integrate computational analysis with experimental research.
Post-doctoral researcher
Naples, Italy
University of Naples Federico II
August 2024
-Present
Multidisciplinary scientist specialising in data-driven analysis of biomolecular systems. I design, run, and analyse molecular dynamics simulations (GROMACS, OpenMM) using advanced sampling techniques (T-REMD, Metadynamics). I transform complex simulation data into insights using Python (NumPy, Pandas, Matplotlib, Seaborn), clustering, statistical analysis, and machine learning pipelines, and automate workflows with Bash scripting. My work enables quantitative understanding of protein, protein-DNA, and membrane systems, and results are communicated through publications and presentations.
Research Assistant
Auckland, New Zealand
University of Auckland
April 2024
-August 2024
Applied computational and data-driven methods to support the design and optimisation of drug linkers for Parkinson’s disease. Leveraged Python scripting, molecular simulations, and statistical analysis to predict potential drug binding sites and guide rational linker design. Combined expertise in protein and small-molecule chemistry with quantitative modelling to inform decisions and optimise molecular candidates.
University Teaching Assistant
Auckland, New Zealand
University of Auckland
May 2020
-August 2024
Gaining experience in an academic environment, supervising labs and marking assignments for undergraduate courses.
Doctor of Philosophy (majoring in Chemistry)
Auckland, New Zealand
University of Auckland
May 2020
-April 2024
Topics: Molecular dynamics simulations (GROMACS, OpenMM), advanced sampling (T-REMD, Metadynamics), data analysis and visualisation (Python: NumPy, Pandas, Matplotlib, Seaborn), clustering, workflow automation (Bash scripting). Focus: Computational modeling of biomolecular systems, advanced sampling techniques, trajectory analysis, and automation of simulation workflows; communicated results through publications and conference presentations.
Bachelor of Science (with First Class Honors, majoring in Biochemistry)
Christchurch, New Zealand
University of Canterbury
January 2019
-November 2019
Python
GROMACS
OpenMM
Bash Script
Linux Administration
Scikit-Learn
Numpy
Matplotlib
SQL
Git, CI, Jupyter Notebooks, Anaconda, Linux, Bash
R Programming
HPC environments
OpenCV
Pandas
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