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11 followers · 10 following
  • Osaka Metropolitan University
  • Osaka, JP

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Achievement: Pull Shark

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Achievement: Pull Shark

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@uob-positron-imaging-centre

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BenDJenkins/README.md

Hi there 👋 I'm Ben Jenkins

I'm a postdoctorate researcher with a background in Chemical Engineering working on the application of granular material simulations to advanced solid state battery manufacturing to develop the next-generation of advanced batteries for EVs.

My github stats
  • 🔭 I am currently a postdoctorate researcher with a fellowship from the Royal Society and JSPS.
  • 🌱 I am blending my knowledge of DEM simulation with deep knowledge of powder materials.
  • 💬 I love everything about space and rocketry as well as electronics and microcontrollers!
  • ‍🎓 I am currently learning advanced Julia for optimal code performance and researching calibration of complex DEM simulation contact models such as the EEPA with limited experimental data.

Skills

  • Mastery over several DEM packages including LIGGGHTS, Blaze-DEM and EDEM, and development knowledge of DEM engines in Stella.
  • Proficient in Python, Julia and data visulisation. I love making super pretty scientific graphs, which are also efficient at conveying knowledge and meaning.
  • Extensive knowlege of machine learning for regression based tasks using scientific data in Python with some new expereince with Julia.
  • Expertise in big data analytics and statistics like principal component analysis, sensitivity analysis and developing custom scripts for filtering data.

Pinned Loading

  1. uob-positron-imaging-centre/DigitalTwins uob-positron-imaging-centre/DigitalTwins Public

    Collection of peer-reviewed Digital Twins developed at the University of Birmingham in partnership with industrial collaborators.

    Python 19 5

  2. granudrum_analysis granudrum_analysis Public

    Python package for use with analysing data from the GranuDrum powder characterisation tool digital twin.

    Python 1

  3. machine-learning-study machine-learning-study Public

    A benchmark study of machine learning models on a granular material dataset for a future paper.

    1