{"id":1365187,"url":"https://alion.io/job/lsu-research-associate-5","title":"Research Associate 5","company":{"id":5304,"name":"Louisiana State University","domain":"lsu.edu","url":"https://alion.io/company/lsu","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":80,"open_postings":57,"ghost_share":0,"stale_share":0.982,"repost_share":0,"time_to_fill_p50_days":20,"computed_at":"2026-10-30T05:48:23Z"}},"role":"Science & Research","role_family":"Science & Research","seniority":"junior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":50000,"max_usd":105000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":849},"experience_years_min":2,"visa_sponsorship":true,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Knowledge Distillation","optional":false},{"name":"Machine Learning","optional":false},{"name":"Model Distillation","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"Multimodal AI","optional":false},{"name":"Sensor Fusion","optional":false},{"name":"C++","optional":true},{"name":"JAX","optional":true},{"name":"Python","optional":true},{"name":"PyTorch","optional":true},{"name":"TensorFlow","optional":true},{"name":"TensorFlow C++","optional":true}],"status":"live","first_seen_at":"2026-09-11T00:00:00Z","employer_posted_date":"2026-09-11","last_verified_at":"2026-10-30T05:40:38Z","board_verified":true,"closed_at":null,"days_open":49,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":49},"description":"All Job Postings will close at 12:01a.m. CST (1:01a.m. EST) on the specified Closing Date (if designated).\nIf you close the browser or exit your application prior to submitting, the application progress will be saved as a draft. You will be able to access and complete the application through “My Draft Applications” located on your Candidate Home page.\nJob Posting Title:\nResearch Associate 5Position Type:\nOther AcademicDepartment:\nLSUAM Engineering - School of Electrical and Computer Engineering (Shuangqing Wei (00007502))Work Location:\n3325 Patrick F. Taylor HallPay Grade:\nOther AcademicJob Description:\nThis position will be responsible for conducting and coordinating research for the federally funded project \"Decision-Driven Information Distillation for Multi-Agent Autonomy\" through studying how teams of autonomous agents operating under partial observability, limited memory, constrained communication, sensing uncertainty, and adversarial interference should filter, retain, represent, and share information so that downstream decisions remain effective and trustworthy.\n60% Research and Algorithm Development:\nConduct research supporting autonomous multi-agent systems that must operate with incomplete observations, limited communication, constrained computing resources, and unreliable data.\nDevelop and evaluate methods that help agents determine which observations to retain, how to update mission-relevant beliefs, what information to store, and when to share information with teammates.\nAdapt suitable estimation, control, machine-learning, and communication methods to the project's multi-agent object-search scenarios.\nImplement these methods in a reproducible software framework and connect the information-processing components to a fixed downstream planner.\nBuild and extend computational multi-agent object-search environments formulated as POMDP or Dec-POMDP problems, with noisy multimodal observations, intermittent communication, spoofed sensor inputs, corrupted messages, communication denial, and dynamic risk fields.\nEvaluate the resulting methods through numerical experiments, benchmark comparisons, and simulation studies in multi-agent POMDP environments, with emphasis on mission outcomes, belief quality, communication\nand memory use, robustness, scalability, and decision latency.\nReview relevant research, software, and simulation tools as needed to support the project's technical development.\n35% Project Integration, Documentation, and Research Coordination:\nIntegrate the project's filtering, belief-estimation, memory, communication, and decision-interface components into a reproducible computational framework.\nWork with faculty, graduate students, and other project personnel to plan simulation studies, coordinate technical tasks, and support the development of the project's computational demonstrator.\nMaintain simulation configurations, source-code repositories, software environments, model checkpoints,simulation logs, benchmark instances, and evaluation scripts needed for reproducibility.\nPrepare peer-reviewed manuscripts, technical documentation, presentations, benchmark releases, software releases, and monthly, quarterly, or annual project reports as required.\nAssist with project planning, milestone tracking, technical reporting, and the development of related research proposals.\nCollaborate with the project team to translate theoretical and computational ideas into a validated simulation-based demonstrator for multi-agent autonomy.\n5% Perform other research-related duties as assigned.\nMinimum Qualifications:\nMaster's degree in electrical engineering, robotics, computer engineering, mechanical engineering, systems and control, computer science, applied mathematics, computational mathematics.\n2 years of relevant research experience.\nRelevant experience may include work in autonomous systems, robotics, estimation and control, machine learning, data assimilation, sensor fusion, or scientific computing.\nA Ph.D. in a related field may substitute for the required professional or research experience.\nPreferred Qualifications:\nPh.D in electrical engineering, robotics, computer engineering, mechanical engineering, systems and control, computer science, applied mathematics, computational mathematics, statistics, or a closely related field.\n2 yeas of relevant research experience\nPreference will be given to applicants who demonstrate strength in one or more of the following:\nResearch experience in robotics, autonomous systems, multi-agent systems, or related simulation environments.\nExperience with estimation, data assimilation, sensor fusion, control, or decision-making under uncertainty.\nExperience applying machine-learning or probabilistic methods to sensor data, belief estimation, information selection, or communication.\nStrong programming skills and experience developing reproducible computational experiments; experience with Python and tools such as PyTorch, JAX, TensorFlow, or C++ is beneficial\nA record of research productivity appropriate to the candidate's career stage, together with strong communication skills and the ability to work collaboratively.\nApplicants may bring depth in a complementary part of the project rather than across the full range of topics. Candidates from engineering, robotics, computing, control, or computational mathematics backgrounds are encouraged to apply.\nAdditional Job Description:\nSpecial Instructions:\nThis is a full-time research position supported by a multi-year project. The initial appointment is expected to be for one year, with continuation contingent upon satisfactory performance, project needs, and availability of funding. The successful candidate will have opportunities to publish theoretical and computational research, develop publicly releasable software and benchmark datasets, collaborate across LSU Engineering and Mathematics, and mentor graduate students.Sponsorship: This position is not eligible for sponsorship.\nApplicants should attach the following materials:\n1. Curriculum vitae;\n2. Cover letter describing the applicant’s research background and fit for the position;\n3. A research statement of no more than two pages;\n4. Contact information for three professional references, including name, title, telephone number, and e-mail address; and\n5. A copy of graduate transcripts. Official transcripts will be required prior to hire.\nApplicants may also attach one or two representative publications or preprints.\nFor questions regarding this position, please contact Dr. Shuangqing Wei at .\nThis position is considered a research or research-related support position and must undergo screenings per RS 17.\nSkills Needed:\nPreferred Skills:\nPosting Date:\nSeptember 11, 2026Closing Date (Open Until Filled if No Date Specified):\nMarch 10, 2027Additional Position Information:\nBackground Check - An offer of employment is contingent on a satisfactory pre-employment background check.\nBenefits - LSU offers outstanding benefits to eligible employees and their dependents including health, life, dental, and vision insurance; flexible spending accounts; retirement options; various leave options; paid holidays; wellness benefits; tuition exemption for qualified positions; training and development opportunities; employee discounts; and more!\nPositions approved to work outside the State of Louisiana shall be employed through Louisiana State University’s partner, nextSource Workforce Solutions, for Employer of Record Services including but not limited to employment, benefits, payroll, and tax compliance. Positions employed through Employer of Record Services will be offered benefits and retirement as applicable through their provider and will not be eligible for State of Louisiana benefits and retirement.\nEssential Position (Y/N):\nLSU is an Equal Opportunity Employer.\nAll candidates must have valid U.S. work authorization at the time of hire and maintain that valid work authorization throughout employment. Changes in laws, regulations, or government policies may impact the university’s ability to employ individuals in certain positions.\nHCM Contact Information:\nFor questions or concerns related to updating your application with attachments (e.g., resumes, RS:17 documents), date of birth, or reactivating applications, please contact the LSU Human Resources Management Office at 225-578-8200 or email . 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