Benjamin Lowe Email & Phone Number

England, United Kingdom

United Kingdom

Japan

東京

• Awarded the highly competitive 1-year post-doctoral scholarship from the Japanese Society for the Promotion of Science (JSPS).• This position continued my PhD research into a new type of biosensor. This position required the ability to work confidently without supervision, and strong problem solving and programming skills. Data analysis and statistical analysis was also required. More specifically: This work involved using simulations of the dynamics of molecules using High Performance Computers (i.e. parallel code run on a supercomputer). Large data files (5-50 GB file size) are generated and therefore I wrote code to process, analyse and visualise the resulting data. This involved regular use of mathematical analysis (e.g. calculating system properties from hundreds of thousands of molecules), statistics (e.g. significance testing, error estimation) and python modules important for Data Analysis and Visualisation such as pandas, numpy, scipy, seaborn and matplotlib.

Southampton, United Kingdom

• This industry-relevant project improved understanding and engineering of a promising, novel type of nanoscale biosensor device. It required me to explore simulation across multiple length- and time-scales, as well as to rapidly achieve proficiency in a wide range of statistical approaches, software and programming languages.• Novel insight into the relevant physics has resulted in several peer-reviewed publications in internationally recognised journals along with presentations at many international conferences. Most recently published a critical review of the field combined with a novel quantitative analysis in the Royal Society of Chemistry’s journal ‘Analyst’ and 'Nanoscale'

東京

• Awarded a placement on the JSPS Summer Programme 2015, a prestigious scheme run by the Japanese Government. This involved a cultural induction followed by a research placement extending upon my PhD topic.• Developed my Japanese and communication skills and learned further simulation techniques. Provided me with the unique opportunity to gain a different perspective on my research and a strong appreciation for Japanese culture and society.• Working with Prof. Y. Shibuta and Prof T. Sakata, this research placement involved large-scale molecular dynamics simulation (data processing, analysis and problem solving), Fortran and Python programming.

Bath, Uk

Synthetic Inorganic Chemistry Lab Project. The work required me to swiftly become proficient in a large variety of air sensitive synthetic techniques that were previously unfamiliar to me and gain experience with analytical techniques such as NMR, XRD, UV-Vis, SEM and EDAX for the characterisation of the clusters and thin-films produced.

A key aim of this role was to provide predictions for how to optimise "affinity" of a molecule to its target. This involves taking a large amount of chemical data and processing it to provide a prediction for what molecular structures are likely to have optimal affinity whilst minimising other factors (such as difficult-of-synthesis and toxicity). The role involved usage of techniques from Data Science, Machine Learning, Chemoinformatics and Bioinformatics. During this placement, I was assigned to a number of projects. I participated in regular team meetings to keep up-to-date on the chemistry being undertaken on each project and understand the team requirements. With this knowledge, I would utilise computational techniques to suggest possible modifications to the drug molecules which might solve key problems, such as toxicity, solubility or potency for each project.I would then present my ideas to Synthetic Chemists, which required me to provide reliable and timely information and be responsive to the chemists and projects requirements. This gave me valuable experience of working effectively in a team.I gained experience in Quantitative Structure Activity Relationship modelling (QSAR) which involves using Data Science techniques to predict the activity of a molecule based on a large dataset. This involved skills such as data processing, linear regression model construction and Principle Components Analysis. The collaboration I undertook with the Shanghai-based group was particularly rewarding. My responsibilities were extensive and involved communication of our problem-solving methodologies. For this work it was essential that I was professional, confident and clear at communicating ideas across a language barrier. To present my results, I chaired several video conferences and maintained a regular email dialogue.

Harlow, Uk

Summer placement in the Computational Chemistry Department at GlaxoSmithKline, I gained valuable experience in computer programming and its application to chemoinformatics, and to the Drug Discovery process.The job required me to compare and contrast two chemoinformatic, computational toolkits, evaluating the benefits and disadvantages of each.I was asked to rapidly acquire familiarity with three programming languages, principally ‘Python’ with some ‘Java’ and ‘UNIX Shell’ Scripting. This was challenging and required initiative as I previously had no direct experience in this area, and was expected to do this largely independently.

Postdoctoral Position, Nanotechnology, Simulation And Data Analysis

Complex Systems Simulation Doctoral Training Centre, 80.1% (Taught Component) 80.0 % (Research Component)

Natural Sciences With Year In Industry, Natural Sciences, First-Class Honours (77%)

Natural Sciences with Year in Industry. Mathematics for Scientists [Maths, Simulation Techniques] (~1/5th) Physical and Inorganic.

A Levels:, Mathematics (A), Chemistry (A), Biology (A), Geography (A), General Studies (A)