Hi there! So, after a long year of applications and interviews, I have the pleasure of joining the QHEAT group (Queen’s High Energy and Astroparticle Theory) at Queen’s University (host to the Arthur B. McDonald Canadian Astroparticle Physics Research Institute). Starting September 2022, I will be pursuing my PhD under the supervision of Prof. Joe Bramante. I am excited to embark on this new journey to explore deeper into the fascinating world of Astroparticle Physics.
I earned my M.Sc. Physics degree from Heidelberg University in Germany. For my master’s thesis, I performed research at McGill University in Canada as a graduate research trainee under the supervision of Prof. Katelin Schutz. My final thesis titled Axion Basinschein : A search for gravitationally bound solar axions via stimulated decay into photons will be posted soon on the website!
Before Heidelberg, I graduated with a B.Sc in Physics from Leipzig University in Germany. During my undergraduate years, I worked as a teaching assistant in Theoretical Physics, Mathematics, and Experimental Physics, totalling over 250 hours of undergraduate-level classroom teaching. My final bachelor’s thesis had the topic Black holes, Singularity theorems and the Global Structure of Spacetime.
The primary purpose of this website apart from who I am and what I have done is outreach. These past five-six years of my life revolved around one thing - Theoretical Physics. While on this incredible journey, there were numerous instances where I had the thought, “if only someone had told me that, I would have saved hours of work” or “that one statement made me understand XYZ.” I want to pass on the wisdom and tools I gained on this journey to my colleagues and anyone trying to decipher the breathtaking world of physics. You can check the “notes” and “literature” tabs. I am also thinking of starting a regular blog about things like my learning techniques, note-taking algorithms, etc. So keep an eye out for that too.
I hope whoever found this website gains something valuable from it. If not, you just got acquainted with another friendly face :)
Ph.D. Physics, Jan 2023 - Ongoing
Queen's University, Canada
M.Sc. Physics, Oct 2020 - Sept 2022
Heidelberg University, Germany
Graduate Research Trainee, Sept 2021 - Sept 2022
McGill University, Canada
B.Sc. Physics IPSP (International Physics Studies Program - IPSP), Oct 2015 - July 2019
Leipzig University, Germany
Final project for a Graduate Statistical Mechanics course
Note: I am assuming that most of you have a high-school level of physics (that is up-to-date and not rusting for years altogether) and went through the foundational mathematical preparation in the IPSP II post.
Here is a brainstormed document of some main things to remember when applying for a Physics Ph.D. program. My search I applied mainly to Canadian and German institutions (with a few exceptions).
If you have read part 1 of this blog, you know that everyone who meets the HEQ criteria in the eyes of Uni-assist gets accepted. Contrary to most good physics programs worldwide, the hard part is not getting accepted to IPSP - it’s survival.
Application to Heidelberg After several wonderful undergraduate years at Leipzig, I applied to one of the best physics faculties on the planet and one of the most fairy-tale-like cities - Heidelberg.
Warning: I graduated from IPSP in 2019 and was a TA until March 2020. Afaik, nothing has changed “drastically” yet since I left Leipzig. If I get any updates, I will try to point them out every time I update this page.
Online certifications from edX and Coursera
Simple, damped & driven harmonic motion, resonance
Coupled oscillators, normal modes and matrix formulation of equations of motion
Vibration of continuous systems leading to derivation of the wave equation and it’s solutions
Various properties of sound and electromagnetic waves
Polarization, waves at interfaces & in media and Interference phenomena
A series of two courses dealing with computer science fundamentals like various algorithms, algorithmic complexities, object oriented programming, data structures, stochastic programming, Monte Carlo simulations and machine learning fundamentals.