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Michele Cascella

Detector software engineer at Lund University

  • Joined: 2018
  • Items posted: 0
  • Profile views: 163

About

Summary

Problem solver, self directed learner, with a 10+ years experience in analysis of large scientific datasets.

Positions

Detector software engineer Oct 2021 -

MAX IV syncrotron, Lund University

X-ray and optical detector, operation, characterization, data analysis, and data acquisition. Support for beamline activities.

Detector Scientist Apr 2018 - Sep 2021

European XFEL GmbH

X-ray detector (CCD, active pixels) data analysis, calibration and performance optimization. On-site and on-call support for experimental activities. Detector documentation authoring and coordination.

Senior Research Associate Nov 2013 - Apr 2018

University College London

Design of the AWAKE spectrometer data acquisition system. Construction and commissioning of the SuperNEMO electron tracker. Member of the SuperNEMO Analysis board. Coordinator for the construction of the SBND UK ultra high voltage feed-through. Teaching assistant and guest lecturer for several courses.

Education

Università di Pisa 2007 - 2011

Field of study: Physics
Degree: Dottorato di ricerca (PhD)

Measurement of the associated production of direct photons and jets with the Atlas experiment at LHC

Skills

Data analysis
Python/ Jupyter/ C++/ C/ SQL/ ROOT/ Git/ CI/CD/ Image processing / Machine Learning / Statistics
Data acquisition
MicroTCA / VME / NIM / LABVIEW
Simulation
GEANT4 / Comsol / Garfield / Pythia / Fluka
Experimental particle physics
Gas based detectors / Semiconductor detectors / Calorimetry
Prototyping
3D CAD / 3D printing / Microcontrollers
Operating systems
Linux / Windows / MacOSX
Document production
LaTeX / Microsoft Office / Open Office / Technical documentation

Keywords: C, C++, CI/CD, Data Analysis , Data Visualisation, Image Processing, Jupyter notebook, Machine Learning, Particle Detectors, Python, Semiconductor Detectors, Statistics

Professional interests

Particle and radiation detector R&D. Data analysis. Machine learning.

Keywords: Data Analysis , Data Science, Machine Learning, R&D

CV

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Contact details

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New opportunities

Open to new opportunities: Yes

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