Pooja Sharma

Hello,

I have recently acquired my Ph.D. degree in Astrophysics from University Paris-Saclay. Right from my Masters's to my Ph.D., I have worked with different tools and software to analyze data.

My research experience has helped me hone my data analysis skills, which encompass finding the optimum way to collect, structure, and analyze data to interpret the underlying information. I believe these skills can easily be transferred to analyzing industrial data to improve customer satisfaction. I have also used statistical tools such as the Monte Carlo Markov Chain method and other statistical tests to fit and compare data.

During my thesis, I was in charge of the R&D activities performed at IJCLab pertaining to the optimization of the calibration system of the camera of the Medium-Sized Telescope (MST) of the Cherenkov Telescope Array (CTA). The optimization involved designing the calibration screen and writing two algorithms; one which allowed determining the optimum path required for the calibration screen to cover the entire camera and the other which allowed finding the position of the calibration screen from the data acquired. Both algorithms were aimed at making the calibration process quicker.

My contribution significantly aided in finalizing the calibration system of the first MST of CTA. I could quickly integrate with the CTA group at the laboratory and worked together with the technical staff as well as collaborators all across Europe. The wide range of topics covered during my thesis, each producing a commendable output, despite the constraints of covid, led my thesis to be nominated for the best thesis award.

IBM’s study revealed that only 28% of manufacturing organizations are using data to draw insights for continuous improvement. Data is the new oil, and Machine learning (ML) methods can help to exploit it. During my Master’s internship, I used an unsupervised ML tool called

FisherEM to find a robust unsupervised classification of the observed data. The algorithm helped reduce the number of exciting observations by regrouping them into classes of similar data. I managed to converge the two different fields of Astrophysics and ML to interpret the information given by each class. My knowledge of unsupervised ML can be adapted to learn similar techniques to understand trends and explore their boundless potential.

I also participated in various international conferences all across Europe, which has helped me develop strong communication skills and experience in explaining technical topics to a general audience. Apart from academics, I was also a part of the organizing committee of CARaDOC,

an organization that aims to bridge the gap between Ph.D. & postdoc researchers and the industry. This experience significantly enhanced my communication and networking skills.

I am autonomous, self-driven and can effectively integrate into a team. I wish to transition into the industrial sector to expand my skills. I believe my research experience would be a great asset to your company. Thank you very much for your time and consideration. I have attached my CV with my application. Please feel free to contact me for further information.

Thank you,

Pooja Sharma

I have worked as a researcher for ~ 5 years. I mainly used python and R. Apart from data analysis, I have also worked in the R&D department to design a part of the telescope (Medium-Sized Telescope of the Cherenkov Telescope Array).

I have a Ph.D. in Astrophysics. It largely involved analyzing data and identifying trends to understand the underlying physics using statistical and machine learning methods.