Subasish Das

The Artificial Intelligence in Transportation (AIT) Lab at Texas State University is offering research assistant opportunities for motivated PhD and MS students, as well as outstanding undergraduates. The lab focuses on leveraging artificial intelligence and machine learning to address safety-critical transportation research challenges. Projects involve working with large-scale crash data, infrastructure data, multimodal mobility datasets, and developing AI-driven decision support tools for transportation systems. Core responsibilities include developing and benchmarking models for crash severity, driver behavior, and infrastructure risk, building end-to-end machine learning pipelines (from preprocessing to deployment), implementing explainable and trustworthy AI methods (such as counterfactuals, causal inference, and mechanistic AI), contributing to journals and conferences in transportation, AI, and data science, maintaining reproducible research-quality codebases for long-term use and open-source release, and collaborating with interdisciplinary teams across engineering, AI, and policy. Applicants should have strong foundations in artificial intelligence and software engineering, proficiency in Python for deep learning, experience with PyTorch and/or TensorFlow, knowledge of statistical learning, validation, and uncertainty analysis, and experience with large datasets (SQL, Pandas, NumPy) and spatial AI. Strong software practices (Git, documentation, experiment tracking) are required. Preferred qualifications include prior AI or research experience in computer science, statistics, transportation, or related fields, evidence of strong analytics (publications, preprints, competitions, open source), and for PhD applicants, independent methodological research capability, 2 Q1 publications, and 500+ GitHub stars. MS/UG applicants should have excellent coursework, a research mindset, and 1000+ GitHub stars. The research assistantship is renewable for 12–24 months based on performance. The specific stipend amount and tuition coverage are not mentioned. The start date is flexible. Interested candidates should send a brief introduction, CV, and links to GitHub, Google Scholar, or prior work (if available) to Dr. Subasish Das at [email protected].

The Artificial Intelligence in Transportation (AIT) Lab at Texas State University is offering Graduate Research Assistant (GRA) opportunities for motivated M.S. students in Civil Engineering. The positions focus on transportation engineering and artificial intelligence, supporting safety-critical transportation research. Students will work on developing and benchmarking models for crash severity, driver behavior, and infrastructure risk, and will implement explainable and trustworthy AI methods such as counterfactuals, causal inference, and mechanistic AI. Collaboration with interdisciplinary teams across engineering, AI, and policy is expected. Applicants should have a strong foundation in transportation engineering and artificial intelligence, with proficiency in Python for deep learning and experience handling large datasets using SQL, Pandas, and NumPy. The GRE is a mandatory requirement for the application package. Preferred qualifications include prior AI or research experience in computer science, statistics, transportation, or related fields, and evidence of strong analytics such as publications, preprints, competitions, or open source contributions. The M.S. in Civil Engineering at Texas State University emphasizes practical, industry-driven projects or theses related to real-world engineering applications, often in partnership with local industries. Students will confront substantial, open-ended problems, perform detailed research, develop and implement solutions, and communicate their findings professionally. Funding is provided through GRA positions, though specific details regarding stipend or tuition coverage are not mentioned. Interested candidates should review the AIT Lab projects and apply via the official application site, ensuring that GRE scores are included in their application package. For more information, candidates may contact Professor Subasish Das or visit the provided links.

Ph.D. opportunity at Texas State University in the Artificial Intelligence in Transportation (AIT) Lab, led by Associate Professor Subasish Das. The opening is for one doctoral student starting Spring 2027 as a Doctoral Research Assistant (DRA). The research focus combines civil engineering , transportation safety , transportation operations , and computer science -oriented agentic AI . Topics mentioned include crash and traffic data analysis, evaluating countermeasures, assessing roadway performance, tool calling, retrieval-augmented generation (RAG), multi-agent workflows, model evaluation, Python, GitHub project replication, AI-assisted coding, AWS, Colab, Docker, GPU computing, and building web tools and APIs. Eligible applicants should hold a B.Sc. or M.S. in Civil Engineering, Computer Science, Computer Science and Engineering, or Computer Engineering. The post emphasizes strong writing, reproducible research, independent problem-solving, ownership, and the ability to develop and ship usable products. Admissions requirements listed in the post include GRE, with preferred scores of Verbal ≥146 and Quantitative ≥160. English proficiency can be demonstrated by TOEFL iBT ≥78 (or ≥4 on the new scale), IELTS Academic ≥6.5 overall with ≥6.0 per section, or another TXST-approved English test. To apply, email your CV, GitHub/portfolio, writing sample, and brief research interests to [email protected]. The post also links to the lab page and the Texas State University Civil Ph.D. page for more information.