CV: Research Fellow

 


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Personal information
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Candidate Profile
 Date Submitted:16-02-2015
 Last Modified:16-02-2015 (04:44)
Job information
 Current job:Research Fellow
 Employment Term:Temp/Contract
 Job location:Anywhere
 Date available:within 3months
 Industry:,
 KeywordsHigh-energy astrophysics Detector calibration Data analysis Simulations
CV

Current position

Co.Co.Pro contract (research fellow) atUniversity of Perugia, Italy. Carbon Footprint and environmental sustainability.

Past positions

2011 – 2012: Postdoctoral research associate at the Michigan Technological University, MI, USA. Calibration of the HAWC Observatory and analysis of Milagro data.

2012 – 2014: Research fellow at University of Perugia, Italy. Development of algorithms and software for the computation of the carbon and water footprint.

Education

PhD in Energy Engineering, obtained at the University of Perugia, Italy, 2015. Thesis title: “Environmental footprinting based on LCA approach: application to carbon, water, land-use, and energy footprint analyses”.

PhD in Physics, obtained at the University of Perugia, Italy, 2010. Thesis title “Search for  Gamma-ray Emission from Dark Matter Annihilation in Galactic Satellites with Fermi”.

Master's Degree in Physics, Elementary Particle, obtained at the University of Perugia, 2007. Thesis title: “Study of the performances of the tower of Glast with particle beams”.

Bachelor's degree in Physicsobtained at the University of Perugia, 2003. Thesis title “Techniques of data reduction for X-ray extragalactic astronomy. The case of the Chandra observatory”.

Participation to international scientific collaborations

Fermi-LAT collaboration, Dark Matter and New Physics group, 2006-2011 (http://fermi.gsfc.nasa.gov/)

Milagro collaboration 2011-2012 (http://umdgrb.umd.edu/cosmic/milagro.html)

HAWC collaboration 2011-2012, Calibration team (http://www.hawc-observatory.org/)

Specific informatics knowledge

Advanced use of C++ and Python programming languages and ROOT analysis program applied to data analysis and data reduction.


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