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Research Assistant (RA) positions

The Remote Sensing and Modeling research Lab in the Kimbell School of Geosciences at Midwestern State University (MSU) has multiple part-time Research Assistant positions available for the 2024-25 academic year. The successful candidate will work closely with Dr. Kashif Mahmud on projects related to remote sensing, hydrogeology, groundwater, terrestrial carbon cycle, and climate change.

Successful candidates should be undergraduate/graduate students in geoscience, environmental science, computer science, or a related field at MSU. Previous computational experience is preferred but not required. The research projects involve basic knowledge and skills in computation, remote sensing, modeling, hydrogeology, and carbon cycle.

What you get:

Experience working with remote sensing, computation, modeling, etc.
Part-time Research Assistant position for 2024-25 (Potential 2025 Summer RA positions)
Option to enroll in Internship courses: either 3-credit hours ENSC 4103 or 0-credit hour STEM 4900
Potential MSU 2024 EURECA Grant – $1000
Possible MSU Summer 2025 UGROW project – $1000

Graduate students

For students interested in M.Sc. in Environmental Sciences and Geosciences, I have funding opportunities and several potential projects to work on. See my Research Page to get an idea of the work I do. If you are interested in working with me, please send me an email with your CV and research interests.

General information about the Geosciences graduate program is here. Graduate Assistantships are available on a competitive basis for full-time students through the college and the department. There are many internal and external scholarships available that apply to students in our program. Please see this page for more FAQs about our program. More information about the Graduate School at MSU Texas is here.

There are many undergraduate and graduate research grant opportunities in the U.S. Learn more about all these specific programs, eligibility, and how to apply from the links provided on this page. Every year, the Geological Society of America (GSA) distributes hundreds of thousands of dollars in grants and scholarships to help further the future of the geosciences. Since 1922, the Sigma Xi Grants in Aid of Research (GIAR) program has provided undergraduate and graduate students with valuable educational experiences. By encouraging close working relationships between students and mentors, the program promotes scientific excellence and achievement through hands-on learning and funding support.

More funding sources, particularly for cave and karst research which I would encourage my students to apply: for example, Cave Research Foundation - Graduate research grant program; Cave Conservancy Foundation - Academic fellowships in karst studies for graduate students; National Speleological Society – Research grant / Conservation grants for students. The National Cave and Karst Research Institute (NCKRI) in New Mexico also conduct, support, facilitate, and promote programs in cave and karst research.

Moreover, The American Society for Photogrammetry and Remote Sensing (ASPRS) offers postgraduate funding with the mission to advance knowledge and improve understanding of mapping sciences to promote the responsible applications of photogrammetry, remote sensing, geographic information systems and supporting technologies.

Proposed topics for Masters thesis

Cave exploration with emerging techniques

This research direction will utilize LiDAR surveys for various cave projects: such as to map the extent of cave damage by touristic exploitation, perform assessment and environmental management of tourist caves using recurrent LiDAR surveys. Repetitive LiDAR measurements could also be used to measure speleothem growth rates in environments where this growth is extremely fast. Furthermore, cave drip logger data can be useful to constrain water balance in hydrological models by combining a drip logger network with surface weather station and soil moisture network. Moreover, combining drip loggers with surface geophysics data could be more informative to track water movement in karst aquifers.

Application of remote sensing to characterize earth surface features

This project will use unmanned aircraft system (UAS) remote sensing data to map earth surface features to characterize its properties, or understand the changes in ecosystems, hydrology, forestry and so on. The project would address scientific questions using remote sensing data targeting the dynamics of earth systems due to unexpected disturbances or gradual changes. One example would be to investigate cave sites around Texas. Another example could be to map the forest canopy to understand its dynamics and eventually improve the prediction of the carbon cycle.

Improving estimates of remote sensing data products

Remote sensing provides a means of observing hydrometeorological state variables over large areas. Few examples are land surface temperature from thermal infrared data, surface soil moisture from passive microwave data, snow cover using both visible and microwave data, water quality using visible and near-infrared data and estimating landscape surface roughness using LiDAR. Novel techniques need to be developed and improved for estimating the hydrometeorological fluxes, evapotranspiration, and snowmelt runoff, using these state variables.

Quantifying climate change impacts and suggesting potential mitigation strategies

In recent decades, changes in climate have caused impacts on natural and human systems on all continents and across the oceans. Impacts are due to observed climate change, irrespective of its cause, indicating the sensitivity of natural and human systems to changing climate. Therefore, I am keen to understand and quantify various climate change impacts on both human and natural systems (such as forestry, agriculture, human health, biodiversity, ecosystem, and environment). Once we identify the impacts, the next step would be to provide solutions for reducing the effect, ranging from reducing the reliance on fossil fuels to reducing population growth at local to global scale.

Multiple point geostatistics in remote sensing

I am interested to solve various challenges in remote sensing data by applying stochastic image analysis and geostatistical methods. Despite having large coverage and degree of detail, the remote sensing data can be of insufficient quality or resolution for many applications. A few challenging cases could be filling missing gaps, fusing data across scales, etc. I have particularly worked on geostatistical methods based on training images which I plan to exploit with the students to improve remote sensing data quality.

Characterize large-scale hydrogeological properties

The project will generate large-scale hydrogeological properties using numerical modeling and remote sensing investigation. The idea is to utilize image-based modeling to form a novel framework with the aim to generate a larger synthetic cave system which may allow the scientists to investigate various hydrogeological properties on an advanced larger scale. The project would aim to provide a more accurate identification of large-scale subsurface flow variability, both spatially and temporally.

Quantifying terrestrial carbon cycle via DA

This project will focus on studying vegetation-environmental change feedbacks utilizing a wide range of remote sensing and in-situ data streams to ensure these processes are adequately represented in terrestrial biosphere models and have improved prediction of global C sink.

Model-Data assimilation to quantify the effects of climate change on plant physiological processes

I am very enthusiastic to see the DA approach I developed being applied to other plant manipulative experiments to untangle the impacts of all physiological and biochemical processes on plant growth due to various environmental changes. This would help us to understand how forest ecosystems respond to climate change and human activities.