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tristanmanchester/README.md

Tristan Manchester

I'm Tristan - a materials scientist specialising in X-ray imaging techniques.

About Me

I'm currently a Postdoctoral Research Associate at Diamond Light Source, where I develop novel instrumentation and software tools for synchrotron X-ray imaging. My work focuses on:

  • Developing advanced imaging capabilities including X-ray laminography
  • Creating deep learning solutions for scientific image analysis
  • Building experimental equipment for in situ materials characterisation
  • Supporting visiting scientists with data collection and analysis
ML Segmentation Deep Learning Segmentation Python Art

Technical Skills

Scientific Computing

  • Python development for data analysis and automation
  • Machine learning frameworks (PyTorch, scikit-learn)
  • Image processing and computer vision
  • High-performance computing

Materials Characterisation

  • Synchrotron X-ray techniques (tomography, laminography, XANES)
  • Laboratory X-ray computed tomography
  • Electron microscopy (SEM, FIB)
  • In situ experimentation

Engineering

  • CAD design (Fusion 360)
  • High-temperature polymer 3D printing
  • Experimental apparatus design
  • Flow cell design

Get in Touch

Currently working on advancing battery research through the Faraday Institution SOLBAT initiative

Pinned Loading

  1. ScrambledSeg ScrambledSeg Public

    SegFormer deep learning pipeline for synchrotron tomography segmentation.

    Python

  2. data_worsener data_worsener Public

    Makes nice lab-based μXCT data look like not nice synchrotron μXCT data for training a segmentation neural net.

    Python

  3. ParticleSegmentation ParticleSegmentation Public

    Particle segmentation from a 3D dataset, using k-means clustering and watershed segmentation.

    Python

  4. pylomap pylomap Public

    Forked from WilliamMAPearson/PYlomap

    Visualisation tool for QIIME2 Data.

    Python

  5. some_nice_python_art some_nice_python_art Public

    Python

  6. VolumeCrop VolumeCrop Public

    Python