I would greatly appreciate feedback on this statement of interest I wrote for a PhD position on Antarctic Climate Causality at KU Leuven. Some of the names and identifying information has been blanked out but I think that does not affect the readability of the text.
There were no specific prompts or word limits for this statement.
I am a Physics graduate with a minor in computer science from the National Institute of S E R, city (NISER). I have been working as a climate science student for two years, measuring turbulent fluxes in the Oak and Pine forests in the Himalayas and studying heatstress and extreme heat characteristics in the tropics. I am writing to express my interest in this PhD position studying causal relationships in the Antarctic. I wish to pursue a research career studying atmospheric processes and the evolution of sensitive landscapes in response to the changing climate. The confluence of expertise and diverse work packages outlined in this position indicates an opportunity to learn enormously in the fields of atmospheric, ice and ocean modelling, and in the application of advanced data processing methods to find causal inferences. An all-round experience in modelling and analysis will be a significant step towards achieving my academic goals. I would be able to apply this experience to further understand the Antarctic system or to study other regions that will benefit from the same treatment.
I had the seed of curiosity regarding our climate at a very young age, I found online communities and grew up consuming a lot of climate conscious media. Ever since I have been fascinated by the descriptions of climate change given in these shows. I joined the School of Earth and Planetary Sciences (SEPS) at NISER to learn how the observations of the weather and the atmosphere get turned into predictions about Earth's changing climate and how we can work towards mitigating its impact. At SEPS I gained diverse experience in atmospheric and climate science, studying heatstress in the tropics and turbulent fluxes in the Himalayan forests.
Investigating the characteristics of humid heat waves in the Indian subcontinent for my master's thesis, I gained proficiency in processing large reanalysis and satellite data products to extract useful insights and visualisations. This was vital in the efficient testing of various hypotheses as our research questions gradually developed into the study of a latitudinal varying heat stress response to atmospheric water vapour seen in the tropics. We explained a negative correlation between atmospheric water vapour and surface temperature in certain latitudes, challenging the established notion that this effect was entirely due to surface processes. We showed how the negative correlation response was closely related to cloud formation characteristics in the region and how this could be important for the evolution of heat stress characteristics of these regions.
I continued to develop visualisation and data processing tools as I transitioned into a research assistant role in the project measuring and modelling Oak and Pine forests in the Himalayas. I was responsible for acquiring turbulent flux data from the remote installations and creating usable documentation and flux products from them. I was able to collaborate with hydrologists, ecologists and atmospheric scientists to better understand how the forests are evolving with the changing climate. It was most interesting to note how all of these changes fed back into one another to create the circumstances that are threatening the local population and ecosystem. The work I contributed in this inter-disciplinary research effort was very satisfying, it will lead to more accurate modelling of the region which will enable insight into the future of the challenges faced by the region. Going on a field trip into the Himalayas was also a great motivator for me to decide that I want to continue to work towards understanding how climate change is going to affect sensitive environments such as this.
In both the projects described above I also learned how to run and use the OLAM global climate simulation. I was able to reproduce the observed heat stress response in the model to more precisely probe the atmospheric processes that may be responsible for the variable response seen. I also helped in the preliminary setup of the same model with regionally finer grids to develop an improved parameterisation for the Oak and Pine Himalayan forests derived from the turbulent fluxes measured experimentally. From my research into Prof. Z's work, this project seeks to use machine learning methods in addition to modelling tools, for the analysis of observation and model datasets and that is where the causal inferences will be derived. I have had an interest in machine learning for a long time, I developed a procedural level generator for the game "Portal 2" using GANS to train the generator to learn the internal logic of a solvable level in the game, which had not been previously done for game level generation. During my project studying heat stress in the tropics, I had ideas to implement machine learning to accelerate the identification of what variables sufficiently describe any particular climatic pattern, providing supporting evidence for certain hypotheses. Due to a lack of institutional knowledge of such methods, I was not able to pursue that development. In this position at KU Leuven, I would be able to build upon my skills both in the domain of climate modelling and in machine learning methods.
I find this to be an extremely exciting opportunity to study the incredible Antarctic landscape. I believe I bring a unique perspective and am highly motivated to embed myself into this collaborative research environment and begin work understanding the Antarctic system. I look forward to working with Prof. X, Prof. Y and Prof. Z, benefitting from their expertise in the respective fields and seeing how I can contribute to the research at hand.
There were no specific prompts or word limits for this statement.
I am a Physics graduate with a minor in computer science from the National Institute of S E R, city (NISER). I have been working as a climate science student for two years, measuring turbulent fluxes in the Oak and Pine forests in the Himalayas and studying heatstress and extreme heat characteristics in the tropics. I am writing to express my interest in this PhD position studying causal relationships in the Antarctic. I wish to pursue a research career studying atmospheric processes and the evolution of sensitive landscapes in response to the changing climate. The confluence of expertise and diverse work packages outlined in this position indicates an opportunity to learn enormously in the fields of atmospheric, ice and ocean modelling, and in the application of advanced data processing methods to find causal inferences. An all-round experience in modelling and analysis will be a significant step towards achieving my academic goals. I would be able to apply this experience to further understand the Antarctic system or to study other regions that will benefit from the same treatment.
I had the seed of curiosity regarding our climate at a very young age, I found online communities and grew up consuming a lot of climate conscious media. Ever since I have been fascinated by the descriptions of climate change given in these shows. I joined the School of Earth and Planetary Sciences (SEPS) at NISER to learn how the observations of the weather and the atmosphere get turned into predictions about Earth's changing climate and how we can work towards mitigating its impact. At SEPS I gained diverse experience in atmospheric and climate science, studying heatstress in the tropics and turbulent fluxes in the Himalayan forests.
Investigating the characteristics of humid heat waves in the Indian subcontinent for my master's thesis, I gained proficiency in processing large reanalysis and satellite data products to extract useful insights and visualisations. This was vital in the efficient testing of various hypotheses as our research questions gradually developed into the study of a latitudinal varying heat stress response to atmospheric water vapour seen in the tropics. We explained a negative correlation between atmospheric water vapour and surface temperature in certain latitudes, challenging the established notion that this effect was entirely due to surface processes. We showed how the negative correlation response was closely related to cloud formation characteristics in the region and how this could be important for the evolution of heat stress characteristics of these regions.
I continued to develop visualisation and data processing tools as I transitioned into a research assistant role in the project measuring and modelling Oak and Pine forests in the Himalayas. I was responsible for acquiring turbulent flux data from the remote installations and creating usable documentation and flux products from them. I was able to collaborate with hydrologists, ecologists and atmospheric scientists to better understand how the forests are evolving with the changing climate. It was most interesting to note how all of these changes fed back into one another to create the circumstances that are threatening the local population and ecosystem. The work I contributed in this inter-disciplinary research effort was very satisfying, it will lead to more accurate modelling of the region which will enable insight into the future of the challenges faced by the region. Going on a field trip into the Himalayas was also a great motivator for me to decide that I want to continue to work towards understanding how climate change is going to affect sensitive environments such as this.
In both the projects described above I also learned how to run and use the OLAM global climate simulation. I was able to reproduce the observed heat stress response in the model to more precisely probe the atmospheric processes that may be responsible for the variable response seen. I also helped in the preliminary setup of the same model with regionally finer grids to develop an improved parameterisation for the Oak and Pine Himalayan forests derived from the turbulent fluxes measured experimentally. From my research into Prof. Z's work, this project seeks to use machine learning methods in addition to modelling tools, for the analysis of observation and model datasets and that is where the causal inferences will be derived. I have had an interest in machine learning for a long time, I developed a procedural level generator for the game "Portal 2" using GANS to train the generator to learn the internal logic of a solvable level in the game, which had not been previously done for game level generation. During my project studying heat stress in the tropics, I had ideas to implement machine learning to accelerate the identification of what variables sufficiently describe any particular climatic pattern, providing supporting evidence for certain hypotheses. Due to a lack of institutional knowledge of such methods, I was not able to pursue that development. In this position at KU Leuven, I would be able to build upon my skills both in the domain of climate modelling and in machine learning methods.
I find this to be an extremely exciting opportunity to study the incredible Antarctic landscape. I believe I bring a unique perspective and am highly motivated to embed myself into this collaborative research environment and begin work understanding the Antarctic system. I look forward to working with Prof. X, Prof. Y and Prof. Z, benefitting from their expertise in the respective fields and seeing how I can contribute to the research at hand.
