CV

Education

PhD Biological Sciences, Queen Mary University of London, 2022-2026
- Thesis: Inferring Demographic and Transmission Dynamics from Genomic Sequences
- Bayesian inference and deep learning approaches to infer patterns of disease spread from malaria parasite genomes.
- Supervisors: Prof Richard Nichols, Dr Matteo Fumagalli, Dr Robert Verity, and Prof Alexander Gnedin.
MSc Bioinformatics, Queen Mary University of London, 2021-2022
- Distinction.
BSc (Hons) Natural Sciences, University of Bath, 2018-2021
- Biochemistry major, Chemistry minor.

Bansal, J.K. and Nichols, R.A. (2025). Can genomic analysis actually estimate past population size? Trends in Genetics, 41(7):559–567. DOI: 10.1016/j.tig.2025.04.005 (Open access)

Programming: Python (primary; modular, production-quality), R, Bash, Git, Linux, HPC, Jupyter, LaTeX
Quantitative Modelling: Probabilistic modelling, Bayesian inference, hidden Markov models, transition matrix methods, ODEs, stochastic simulation, uncertainty quantification, sensitivity and scenario analysis, model back-testing and validation, parameter estimation, synthetic dataset generation, time series analysis, machine learning (surrogate modelling, training data generation)
Software & Workflow: Modular production Python, version control (Git), reproducible analytical pipelines, HPC deployment (cluster scheduling, array jobs), collaborative research workflows
Languages: English, Punjabi, Hindi, German

Research Assistant — Simulation & Analytical Modelling, Imperial College London, March 2026-February 2027
- Developed a large-scale stochastic simulation framework in Python to generate high-quality synthetic datasets for training machine learning surrogate models.
- Ran sensitivity and scenario analyses across 10,000+ parameter combinations on HPC infrastructure, validating synthetic outputs against empirical data.
- Built automated, modular Python pipelines adopted by collaborating teams.
Computational Biology Intern, Brunel University London, June-September 2021
- Learned Visual Molecular Dynamics (VMD) through monthly meetings and online tutorials, with the support of Dr Sarath Dantu. Explored PETases and CUTinases, comparing the residues that facilitate catalytic activity, and used trajectories to highlight areas of high protein movement.
Bioimaging Intern, University of Bath, June-September 2020
- Investigated the ROCK signalling pathway as an undergraduate researcher, using bioimaging software including Ilastik and ImageJ. Analysed cells at different stages of the cell cycle and identified the effects of the ROCK inhibitor Y-27, presenting findings to the team in weekly meetings using R.

I have taught and supported students across undergraduate and master’s-level biological sciences modules.

Delivered 200+ hours of teaching spanning a full Python programming module, from fundamentals to object-oriented design. Taught a statistics and simulation module in R covering probability, statistical inference and stochastic modelling, developing practical exercises that made abstract concepts tangible for students from diverse backgrounds.

Module	Topics
Coding and Data Science	Intermediate R, GitHub, and tidy data
Metabolic Pathways	Undergraduate biochemistry
Coding Club	Introductory R
Research Design and Analysis	Introductory R and statistical analysis
AI in Biosciences	SearchGUI and biological networks
Statistics for Biologists	Statistical tests and Bayesian theory
Coding for Bioscientists	Python

Module	Topics
Metabolic Pathways	Undergraduate biochemistry
AI in Biosciences	Cytoscape and SearchGUI

CEE Symposium, LSHTM, September 2025 — Invited speaker
Third Year Symposium, Queen Mary University of London, May 2025 — Best Talk
PopGroup58, Sheffield, January 2025
MASAMB, Queen Mary University of London, August 2024 — Poster
ProbGen24, Vienna Biocentre — Poster
PopGroup57, University of St Andrews, January 2024 — Poster
- Presented the poster “What is knowable about past demography? The limited scope of genomic data analysis”.
- Supported by a Genetics Society travel grant.
Bioinference, University of Oxford, July 2023
PopGroup56, Queen Mary University of London, January 2023
First Year Symposium, Queen Mary University of London, November 2022 — Talk

Analysis of High Throughput Data for Population Genetics, University of Copenhagen, August 2023
Deep Learning for Population Genetics and Phylogeography, online, February 2023

Mitosis Magazine — Featured in a student-led magazine and interviewed on their YouTube channel, sharing advice on PhD applications and experiences as a woman in STEM.
QMUL PhD Spotlight (University Newspaper) — Featured discussing my thesis, research interests, life at QMUL, and extracurricular activities.
QMUL “Made Different” Student Recruitment Campaign — Shared my story as a PhD student and part of a diverse community.
MASAMB24 Committee — Supported speakers and attendees, and organised the post-event social.
Heston Community School — Delivered annual talks encouraging students to pursue scientific careers, and provided support with personal statements.
Genetics Society Symposium Grant (£2,000) — Awarded funding to organise a symposium in November 2026 bringing together malaria researchers and population geneticists.