Nikolai Juraschko | CV

DPhil/PhD in Biochemistry

@University of Oxford, UK
(10/2022 – 04/2026)

Title: Combining MD simulations with ML approaches to facilitate the morphological classification of E. coli in cryo-ET data

Performed large-scale MD simulations of crowded protein systems and ligand binding with GROMACS/Amber and 6 different force fields; analysed with Python on national HPC clusters. Administered data augmentation for affinity-VAE development, linking MD to ML tasks.

MSci Mathematics with First Class Honours

@UCL (University College London), UK
(09/2017 – 07/2021)

Title: Sheaves and Čech Cohomology

BSc Mathematics en route; First Class in every year.
Included CompSci modules on fundamentals of statistical (machine) learning.

Abitur

@Albertus-Magnus-Gymnasium Regensburg, Germany
(09/2014 – 06/2016)

1.0 (top < 2% in Germany)

Research Software Engineer - AI4Science (Prof Khalid Lab)

@University of Oxford, UK
(10/2025 – 03/2026)

Porting DeepDriveMD (ML-enhanced MD simulations for biomolecular systems) from the US SUMMIT supercomputer to UK HPC, new NVIDIA Grace Hopper architecture, and overseeing its deployment. Collaboration with N8 Research Partnership.

Researcher on the Transformative Research Funding Programme

@The Rosalind Franklin Institute, UK
(10/2021 – 09/2025)

Funding Awarded by UKRI-EPSRC

Digital Twin Cell project advancing in vivo science by performing virtual experiments. Led collaboration for the Franklin with UKRI-STFC and The Alan Turing Institute on cryo-ET segmentation; co-authored 2 publications (ECCV & IUCrJ); validated the developed ML tools via a CZI posted Kaggle challenge.

Turing Enrichment Scheme Award

@The Alan Turing Institute, UK
(10/2023 – 06/2024)

Developed and published a Python package for processing protein structure data for downstream simulations and ML model training in an interdisciplinary collaboration with structural biologists and computer scientists.

Data Study Group

@The Alan Turing Institute & National Oceanography Centre, UK
(02/2023 – 03/2023)

Title: Towards a Deeper Understanding of Eddies Using Machine Learning

Managed research project and supervision of 4 PhD students and consulted on applying ML models such as CNNs/(V)AEs and satellite data handling.

Research Experience Placement (Prof Turchyn Lab)

@University of Cambridge, UK
(07/2021 – 09/2021)

Funding Awarded by UKRI-NERC

Title: Carbon Storage in Salt Marsh Environments, a Machine Learning and Field-Based Approach

Pre-processed non-homogeneous satellite data and combined it with biogeochemistry data using Python and QGIS. Analysed data using ML models with Weights & Biases and XGboost.

Paid Internship

@zeroG (IT consultancy), Frankfurt, Germany
(07/2018 – 09/2018)

Learned deep learning frameworks TensorFlow/PyTorch, algorithm development, and machine vision tasks. Acquired knowledge of issues in reliable AI/ML and applied ethical consequences in the aviation field. Delivered product to one of the main aircraft providers worldwide as a client.

Quantitative Biochemistry Class Tutor

@Department of Biochemistry, University of Oxford, UK
(10/2025 – current)

Computational Biochemistry, Mathematics, Data, and Statistics

Women’s Head Coach

@St Anne’s College Boat Club, Oxford, UK
(04/2025 – current)

Led pastoral care and well-being of the athletes, fostering a supportive and resilient team culture. Provided tailored athlete development plans to support technical and physical growth. Led and structured training programmes for first and lower boats, on land and water, and tracked team performance.

Science Editor on Editorial Board

@Pembroke Academic Journal, Oxford, UK
(06/2022 – 07/2025)

Elected Member of the Academic Board

@UCL (University College London), UK
(10/2018 – 09/2019)

Faculty Representative (MAPS)

@UCL (University College London), UK
(10/2018 – 09/2019)

Represented ~51,000 students on the Academic Board and ~2,900 students as the MAPS Faculty Representative.