Dr. Saranya Samik Ghosh

Personal webpage

Welcome to my personal webpage!

I am an Assistant Professor in the Department of Physics at the Indian Institute of Technology Hyderabad (IITH).


I conduct research in the field of High Energy Physics (HEP), that seeks to study the elementary particles that make up the universe and the fundamental forces through which these particles interact.


I primarily work on the Compact Muon Solenoid (CMS) experiment at the CERN Large Hadron Collider (LHC).  

My interests:

• Research on fundamental particles and their interactions in the field of experimental High Energy Physics (HEP), physics of the Higgs boson, Standard Model (SM) measurements and searching for new physics phenomena. 

• Development of particle physics detectors for HEP experiments.

• Communicating physics and scientific research to students and non-experts.

• Applying AI/ML based techniques for research in the field of experimental High Energy Physics.


Opportunities:

• Ph.D. positions: Direct applications via email are welcome from those interested in Ph.D. positions, who have qualified for a JRF position through NET/UGC/CSIR exams.

• Ph.D. positions: GATE qualified candidates are welcome to apply through the IITH application process.

• Ph.D. positions: Ph.D. candidates through external / interdisciplinary routes are welcome to contact via email.

• IITH undergraduate and postgraduate students interested in working on a project are welcome to contact via email. Preference will be given to those interested in experimental particle physics and detector development, followed by those interested in ML based topics.

• External undergraduate and postgraduate students interested in working on a project are welcome to explore opportunities via IITH internship programs such as the SURE summer student program. Externally funded students are also welcome to get in contact via email, preference will be given to those interested in experimental particle physics and detector development, followed by those interested in ML based topics.