Student experience

Image

From: Mexico 

I became interested in numerical modelling and neural networks after finishing my bachelor's degree in physics. After doing some research on master's programmes, I found that the computational applied mathematics programme was a good fit for me because it has a variety of courses that combine theory and practise. In addition, the master's programme has a distinguished faculty. Consequently, I realised I needed to enrol in the CAM programme. 

I enjoyed how the courses were divided between lectures and workshops throughout my studies. Thus, one can reinforce the reviewed theory and ask questions during the workshops. In addition, I was able to choose courses that matched with my interests, and by the end of the programme, not only had I achieved my learning objectives, but I was also able to study exciting areas of mathematics, such as Data Assimilation and Applied SDEs. In addition, the CAM Research skills course assisted me in developing the skills necessary for conducting and presenting scientific research, which I found to be really useful. 

The academic staff is quite helpful. If you have a query about a course or need advice, they can provide assistance. I really enjoyed meeting people from all around the world and establishing friends with them. Moreover, Edinburgh is a great city. When I got the opportunity, I enjoyed seeing the city and jogging in its gorgeous parks. 

During my dissertation, I investigated themes that intrigued me and applied some of the previously examined material. This period of time was the decisive reason in my decision to pursue a PhD. 

Image

From: Romania 

Currently working: as a PhD student at the University of Edinburgh

Georg Cantor once said: “In mathematics, the art of proposing a question must be held of higher value than solving it.” Having studied Mathematics and Computer Science at undergraduate level, I found myself with more questions left unanswered than I started with, and I became increasingly more interested in what lies at the intersection of these two areas. This is exactly what drove me to apply to the CAM MSc. The program not only taught me how to apply my algorithmic thinking skills to ma

thematics, but also how to construct a rigorous mathematical framework for computer science based concepts. As part of the MSc, I filled many gaps in my previous education by studying, for instance, SDEs and optimisation. I also got the chance to further my knowledge in areas like numerical methods and data science. In fact, the optional modules are rather diverse, offering a good balance between introductory and advanced courses. Even though the delivery of the taught component was completely online, I found the tutorials and office hours extremely useful, providing an opportunity to ask questions, as well as a chance to engage with the CAM community. Finally, I got to apply all the skills I gained throughout the year during the dissertation in the summer. This was an excellent research skills exercise and certainly one of my favourite features of the MSc. The program organisation and content is very well complemented by its location. In particular, Edinburgh is a stunning city, whose distinct architecture and vibrant atmosphere make it a fantastic place to live in. This, as well as the community I got to engage with and the knowledge and skills I acquired through the CAM MSc, compelled me to further do a PhD at the University of Edinburgh. 

Image

From: Ireland

Currently working: on a PhD in Mathematical Modelling, Analysis and Computation at the University of Edinburgh

I chose the CAM MSc after studying Applied Mathematics at undergraduate level, where I found myself drawn towards classes with some sort of modelling or computational element to them. I found these classes interesting as they allowed me to apply some of the theory I had learnt, to solve problems that had real world applications. I knew I wanted to continue learning about this area after my undergraduate degree so I searched for MSc's in applied mathematics and came across the CAM MSc. The CAM MSc has a focus on computational work and modelling that is balanced with theoretical work, which was exactly what I was looking for.

The MSc had the added bonus of being in Edinburgh which is an amazing city to live in, with a huge amount to do and see outside of the MSc course itself. As part of the MSc, I really enjoyed the course on Dynamical Systems as it was an interesting way to look at problems, while being particularly relevant to real world applications. The dissertation at the end of the year was a good chance to get to work on an area I was interested in, allowing me to apply some of the material I had been learning all year to a larger project and build research skills in Mathematics.

I really enjoyed meeting new people from the CAM cohort as it was a great way to make friends from different places. The university has a huge array of clubs and societies to meet people interested in the same things you are or to try something new either. Currently I am working on a PhD at the University of Edinburgh and the skills I gained, alongside the material covered on the MSc are relevant all the time in my research.

Image

From: Germany

Currently working: on a PhD in Applied Mathematics at ETH Zurich

I chose the University of Edinburgh because of the wide range of different courses offered in their MSc CAM program, ranging from stochastic differential equations to statistical learning theory. The fact that it is located in arguably one of the most beautiful cities in the world is also a nice side effect. During my studies, I particularly enjoyed the close contact with the academic staff. Whether you are excited about a research idea or simply have questions about the ongoing courses, you can always reach out to them.

I believe that the strong focus on how to conduct mathematical research helped me a lot when I started a PhD at another university and made me confident enough to work on my own research ideas. The historic city, the renowned university and the faculty at the University of Edinburgh provide a fantastic environment to learn and grow, but also to have a wonderful time.  

Image

From: USA

Currently working: as a Data Scientist at Mirador Analytics

I chose to do the CAM MSc as I completed my Bachelor's degree in applied mathematics, so the course was ideal given my academic background and interests. The MSc also allowed for exploring different directions within the discipline, with an emphasis on developing the programming skills necessary for applications. This flexibility and emphasis on programming attracted me to the programme, as I was interested in exploring different areas within applied maths, statistics, and data science.

I especially enjoyed being part of the CAM MSc cohort, as there was a strong collaborative atmosphere between students, and the supervisors were very helpful and supportive. The interaction with professors in workshops and office hours was also very helpful for gaining a strong understanding of the material.

The CAM MSc allowed me to develop many skills that are essential for my current position as a data scientist. I continue to use the programming skills developed throughout the MSc on a daily basis, and the mathematical knowledge and research skills have allowed me to pursue research-oriented work. The research skills course in the second semester was particularly important for gaining exposure to academic research. The final dissertation project also allowed me to gain experience in the field of biomedical data science, which I now work in and thoroughly enjoy.

Image

From: China

Currently working: on a PhD in Computational Science at University of Bristol

My key purpose in choosing CAM in Edinburgh is to continue learning about physical mathematics and mathematical modeling. I wanted to seek knowledge and an environment which would enable me to pursue my interest in studying science-related numerical methods and expand my data analysis capability, and to a lesser extent knowledge of mathematical applications to various scientific fields. 

The program is well designed, containing various courses about scientific computing, programming, and computational statistic. The one I liked best is the CAM research skills training course which gives us an opportunity to learn how to conduct scientific research from the very beginning to the end. The course let us join the weekly seminar to learn the frontier research in the field of applied mathematics, and we wrote a report about one of the speeches we liked the best. We were taught how to make a personal website like a professional researcher and finally, we were divided into four groups and worked together to finish a research paper.

The program has very good courses about numerical ODEs and PDEs. Also, the program focuses on training students the essential skills of scientific programming languages like Python and MATLAB. I worked with Dr. Maximilian Ruffert on my dissertation to study the numerical simulation of the motions of n-body particles. During the two months of study, with the patient guidance of Dr. Ruffert, combining the previous knowledge I learned from the program, I successfully finished my dissertation and found great interest in computational astrophysics. Thanks to CAM, I found a place at the University of Bristol to continue my PhD research in computational science.

Image

From: Ireland

Currently working: as a Senior Quantitative Developer at DV Trading

Having come from a background in theoretical physics,  the aspect I most enjoyed from my studies was modelling real world phenomenon using computers. The CAM MSc provided the perfect blend of theory and application, preparing me for my current research-oriented job in quant finance.

The University of Edinburgh is one of the top universities in the world and what stood out to me most was the high quality of teaching. Courses were very well organised with plenty of resources outside lectures to help one fully understand the material. I use skills learned from the CAM MSc every day in my work. This includes specific course material such as object-oriented programming, optimisation and stochastic calculus, as well as problem solving skills and academic writing.

Image

From: China

Currently working: as an Algorithm Engineer at Ankobot Smart Technologies

 I chose to study the CAM MSc because it is full of possibilities. Many doors have opened for me ever since I went to the University of Edinburgh – I could study dynamical systems which highly correlate with many problems in physics and chemistry; I could also learn statistical programming as a tool to do data science, a popular hit in the job market; the list goes on and on.

There were various subjects to choose for the dissertation, too. In fact, the credit of me getting my current job (as an algorithm engineer) goes directly to my dissertation where I learned how to do image processing and analysis. Generally, I think the CAM MSc is hugely diverse, and I believe that everyone can find something that matches their interests here.