Senior Research Scientist, Information Science – Extended Temporary

This is a fully remote position, open to applicants in United States.

📋 Description

• Take charge of the design, implementation, and assessment of AI/NLP systems for evaluating scientific feasibility.

• Create and test integrated workflows that merge literature-based discovery, structured knowledge extraction, simulation, and code-based experimentation.

• Conduct experiments and benchmarking on a large scale.

• Design and manage research codebases using Python and related tools.

• Develop automated experimentation frameworks, integrate simulations, and set up evaluation infrastructure.

• Ensure the creation of reproducible artifacts, effective logging, and comprehensive documentation for extensive empirical studies.

• Design and perform systematic empirical analyses of model behavior and experimental results.

• Examine large-scale datasets, intermediate outputs, and logs to assess system performance and enhance methodologies.

• Create and conduct user studies focused on human scientific feasibility assessment.

• Lead and co-author papers for prestigious AI/NLP and machine learning conferences and journals.

• Prepare manuscripts for submission to peer-reviewed publications.

• Develop technical presentations and share findings at national and international conferences.

• Establish research directions, experimental methodologies, and project timelines.

• Assist in the preparation of technical reports and research documentation.

• Foster collaboration, manage relationships, and provide technical mentorship to student researchers.

• Collaborate with partners both within and outside the University for joint experiments, data integration, and research dissemination.

• Contribute to a collegial, respectful, and cooperative research atmosphere.

⛳️ Requirements

• Outstanding programming skills, particularly in Python, along with robust software engineering practices.

• Proven ability to design and uphold significant research codebases.

• Strong understanding of AI/NLP research methodologies, which include experimental design, evaluation, and benchmarking.

• Knowledgeable about user studies, IRB protocols, and human subjects research.

• Demonstrated proficiency in hands-on empirical research, with extensive experience in generating and analyzing large volumes of data, intermediate representations, and experimental outputs.

• Familiarity with Linux-based research environments, Git, containerization (e.g., Docker), and reproducible workflows.

• Capability to work autonomously in a research-oriented, small-lab environment.

• Excellent written and verbal communication skills.

🏝️ Benefits

• Opportunity to work on cutting-edge AI/NLP research projects.

• Engage with a dynamic team in a collaborative research setting.

• Access to professional development and training opportunities.

• Competitive salary and comprehensive benefits package.