Arjun Wadhawan – Computational Chemistry

Moving ahead with the Core vs Non-Core series, we have Arjun Wadhawan, a delightful personality, who has completed his doctorate in Computational Chemistry from the University of Amsterdam. Arjun graduated from the Department of Geology and Geophysics, IIT Kharagpur in 2015, worked as a Petro physicist at Schlumberger and soon realized his passion for Computational Chemistry.

1. What prompted you to go to graduate school after working one year for Schlumberger? How has your experience been until now?

After joining Schlumberger, I understood a few things. If you take a job in India, you get to do backend stuff and not much key stuff, and growth opportunities are less. There is also a very cut-throat competition. So, the PhD allowed me to grow scientifically and increased my scope of growth. I got a good PhD chance and my age allowed me to get a PhD. I got selected for the Shell PhD Programme, which allows a full relocation program and gives flight fare to visit family.

2. What were the various options available to you while choosing a career path? How and why did you decide to pursue a career in the field of Computational Sciences? Also, how did you choose your PhD guide?

I realized at Schlumberger that Geology is a niche domain and there are a very limited number of organizations who provide jobs based on geology. But computational science allowed me to do something new, and the scope was not as limited. I picked my professor through the Shell PhD programme, which allows a person to see a professor and project, and put priority on each. So a bit of luck and a little knowledge about the professor allowed me to get my PhD programme.

3. How important is a Letter of Recommendation (LoR) while applying to learn at universities abroad? What role does it play?

When the teacher wants to know about the mentality and the personality of a student, they read the LoR because these are stuff not written in a CV. LoRs are considered imp and sometimes tie breaks are broken based on it. So it’s not a deciding factor, but it does play a role.

4. When and how did you build the required skillsets for getting into the University of Amsterdam? Did you do any internships? Any resources you used to prepare?

I had an internship at Schlumberger itself. Apart from that I did my masters project in KGP. One thing that helped me a lot was I learned Coding and did quite a few projects in computational Physics in Python. For the skill sets, no matter which field you are applying for a PhD, you must have basic knowledge of Python and Matlab from the scientific perspective. Added to this, the ability to write scientific reports and research articles will do the job.

5. You were from the Department of Geology & Geophysics during your undergraduate days, but now, you are in the field of Computational Sciences, which is quite different. So, what impact did your undergraduate department have on your postgraduate studies?

The modern diversification of science subjects has allowed us to work in a wide range of fields. Geology and Geophysics department is also very versatile. It is our department in IIT KGP that played a pivotal role and gave a wide range of opportunities to explore and work on. Also, the IIT stay made me realize that we are not limited to what we are and can do lots of things outside.

6. What changes did you observe between IIT Kharagpur and the University of Amsterdam with respect to the education system, campus environment, research facilities, students’ lifestyle, etc.?

Here in Amsterdam, less population burden has led to comparatively low competition. People are more explicit about their goals. The curriculum is also very flexible and gives one the freedom to explore and pursue many things. The infrastructure and facilities are pretty much advanced.While in KGP, we become academically stronger and diverse. The association with various societies, clubs, cells, etc., improves one’s overall personality and matures to face challenges in real life. Also, the nature of campus life a KGPian goes through produces a bunch of life-long friends with a fantastic bonding.

7. How are the growth opportunities in your field? Could you tell us about your day-to-day job? Do you plan to pursue academic research, or are there research opportunities in corporate as well related to your field?

Once you graduate, you are very open to work anywhere as an algorithm engineer or a design engineer based on your skills. You get an opportunity to collaborate with multiple companies and get to contribute to their research. I also got to work with one of the biggest companies in Europe, which manufactures computer chips as a design engineer. Being a part of this field, we also do a lot of simulations to optimize various parts of the machines using physics-based approaches.

8. What do you think are the major differences between academic research and corporate research jobs? How did you decide which one is best for you?

Academic research has a different goal when compared to the industrial one. Academic research encompasses the necessity of becoming a professor, where you are supposed to do a doctorate and post-doctorates. You have to keep publishing research articles, and it becomes very competitive. The kind of articles and the research also impact your interest. One can’t provide funding if you aim to do research on something that does not resonate with the current demand. The goal is more focused and concrete when you go for industrial Research and Development.

9. What advice/message would you like to give to a student interested to pursue a course similar to yours? Looking back, what would you have done differently?9. What advice/message would you like to give to a student interested to pursue a course similar to yours? Looking back, what would you have done differently?

Students should be well versed with programming, irrespective of the field they are supposed to join. If possible, try to publish a research article to get a feeling of what research is. One could either work with a professor or assist a PhD student in their projects. The whole chain would help you learn a lot, from discovering the problem statement to building up the solution to finally coming up with the code and the theory behind it.