Work with thought leaders and academic experts in Python

Christopher Timms is a highly skilled computational physicist with a Ph.D in Computational Physics from The University of Texas at Dallas. He also holds a Master of Science in computational physics from the same institution. With a strong background in physics and computer science, Christopher has a deep understanding of how to use computational methods to solve complex problems in physics. He has experience working as a Technical Writer/Developer at Amazon Braket, where he was responsible for creating technical documents and developing software tools for quantum computing. Prior to that, he worked as a Research Assistant at The University of Texas at Dallas, where he conducted research in computational physics and published several papers in peer-reviewed journals. Christopher's extensive education and experience make him a valuable asset in any team working on challenging computational physics projects.

Katrina Webb is a highly educated and experienced physicist with a passion for teaching and research. She received her BS in Physics from Texas Tech University in 2022, followed by continuing in the physics PhD program at the same university in 2022. During her time at Texas Tech, she worked as a teaching assistant and student assistant, gaining valuable experience in the classroom and laboratory settings. She also conducted research in various areas, including quantum pedagogy and astronomy, and participated in the High Scholars Research Program at the University of Texas Rio Grande Valley. Katrina's passion for physics and education led her to further her studies and research at the National High Magnetic Field Laboratory, where she worked as a Reu Student. She also gained experience as an astronomical observer at CTMO and continued her research at Texas Tech University. With a strong background in both theoretical and experimental physics, Katrina is a well-rounded and knowledgeable physicist. She is dedicated to sharing her knowledge and skills with others, and her experience in teaching and research has prepared her to effectively communicate complex concepts and ideas. Katrina is committed to making a positive impact on the field of physics and inspiring the next generation of scientists.

A seasoned Decarbonization Researcher with over 13 years of expertise in cutting-edge decarbonization technologies and strategies. Proven track record in post-combustion carbon capture, direct air capture, and blue hydrogen generation. Specialized in low-energy hydrocarbon separation using advanced liquid adsorption techniques and membrane reactor-based methane reforming. Highly proficient in computational tools like Python (parallel computing) and MATLAB, with extensive experience in process modeling software such as gPROMS, Aspen Plus, and CFD tools like Ansys Fluent. Adept at emissions classification, Life Cycle Assessments, and driving sustainability through innovative, scalable solutions in energy and resource management.

I have over 15 years of experience working with advanced statistics and managing databases for large-scale research studies and small businesses. My statistical experience includes an extensive published record using various forms of the generalized linear model (e.g., regression, logistic regression, etc.), psychometrics and scale development, methods for handling missing data (such as multiple imputation), and power analysis. I am proficient with Stata, Python, and Mplus, and I have experience with Tableau, R, SAS, SPSS, and various other software packages. Throughout my career, I have applied this expertise in varied data contexts, including large epidemiological national surveys, experimental data, longitudinal/repeated measure studies, clinical data, and randomized controlled trials. My history of peer-reviewed publication is a testimony to these technical qualifications and documents dozens of successful collaborations with different individuals across multiple projects and institutions.  My experiences working with researchers, clinicians, and other professionals has honed my communication skills and ability to translate complex data into actionable insights for varied audiences. I also understand how to practically apply these experiences in a business context.  In my most recent position at Worth Treatment Center, I led clinic’s neuropsychological testing program and spearheaded the automation of a data pipeline to streamline patient care.  This pipeline transformed electronic form data (e.g., for tests, intakes, & progress notes) into actionable physician decision-aides and integrated patient scheduling and communications.  At the touch of a button, clinic psychiatrists can now generate a report visualizing changes in a patient’s self-reported symptoms alongside changes in their prescribed medications, or that statistically compare a patient’s test score with clinic and national norms.  By streamlining our clinic’s data workflow, these systems decreased the time physicians spent on extraneous aspects of progress notes by 50% and led to a fourfold reduction in the time staff spent on billing and scheduling. Throughout my career, I have particularly enjoyed my experiences in two recurring contexts.  During scientific peer review, I have always relished the challenge of defending my analytic approach with principled, reasoned arguments amongst experts.  Similarly, the process of helping colleagues outside my areas of substantive expertise gain insights into their own data and research – for example, by helping them map their ideas onto quantitative modeling frameworks or visualize patterns that aren’t immediately apparent in the raw data – has always been especially satisfying.  I am interested in opportunities to provide my expertise on problems like this.

José Paulo Marchezi is a highly educated and experienced space physics researcher with a strong physics and data science background. He received his Ph.D. in Space Physics from Instituto Nacional de Pesquisas Espaciais in 2020 after completing a Master's degree in the same field in 2016. He also holds a Full Degree in Physics from Universidade Federal de Santa Maria, which he obtained in 2014. José has gained valuable research experience throughout his career by working at various prestigious institutions. He has served as a postdoctoral research assistant at the University of New Hampshire, a postdoctoral fellow at the State Key Laboratory for Space Weather at INPE, and a researcher at Frontier Development Lab. He has also held positions as a Postdoctoral Fellow and Ph.D. Researcher at the National Institute for Space Research. José's data science and space physics expertise led him to work on important projects, including researching space weather and developing predictive models for space events. He has also worked as a Data Scientist at Dom Rock, where he used his skills to analyze and interpret large amounts of data. In addition to his research and academic work, José has also gained valuable experience as a Visitor Researcher at Goddard Space Flight Center, where he collaborated with other scientists and researchers from around the world. With his strong education and diverse research experience, José Paulo Marchezi is a valuable asset to any team in the field of geofísica espacial and data science.

A Senior Machine Learning Engineer with 8 years of experience in this field. Expertised in Machine Learning, Deep Learning, Large Language Model, Natural Language Processing, Retrieval Augumented Generation, Computer Vision and Data Engineering. Specializing in recommendation engines, predictive analysis system, chatbots, document processing and risk assesment model, combined with a deep understanding of supervised learning, unsupervised learning and reinforcement learning.

numerical modeling, data analysis, scientific software development, scientific writing, simulations on high performance computers