{"id":1492272,"url":"https://alion.io/job/exxonmobil-postdoctoral-researcher-explainable-ai-for-3d-data","title":"Postdoctoral Researcher - Explainable AI for 3D Data","company":{"id":15984,"name":"ExxonMobil","domain":"exxonmobil.com","url":"https://alion.io/company/exxonmobil","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SuccessFactors","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Spring, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":153000,"max_usd":338000,"period":"year","method":"role_country_seniority_unknown","sample_n":4194},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Anomaly Detection","optional":false},{"name":"Computer Vision","optional":false},{"name":"Explainable AI","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"Interpretability","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"TensorFlow","optional":false}],"status":"live","first_seen_at":"2026-08-14T07:00:00Z","employer_posted_date":"2026-08-14","last_verified_at":"2026-10-26T06:03:55Z","board_verified":true,"closed_at":null,"days_open":72,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":72},"description":"About us\nAt ExxonMobil, our vision is to lead in energy innovations that advance modern living while reducing emissions. As one of the world’s largest publicly traded energy and chemical companies, we are powered by a unique and diverse workforce fueled by the pride in what we do and what we stand for.\nThe success of our Upstream, Product Solutions and Low Carbon Solutions businesses is the result of the talent, curiosity and drive of our people. They bring solutions every day to optimize our strategy in energy, chemicals, lubricants and lower-emissions technologies.\nWe invite you to bring your ideas to ExxonMobil to help create sustainable solutions that improve quality of life and meet society’s evolving needs. Learn more about our What and our Why and how we canwork together.\nWhy Join ExxonMobil?\nAt ExxonMobil, we apply advanced optimization and machine learning techniques to solve some of the most challenging problems in energy, manufacturing, and low-carbon technologies. In this role, you will work on cutting-edge methods at the intersection of OR and AI, directly impacting critical business decisions and shaping next-generation computational decision-support capabilities.\nAbout the Role\nExxonMobil is seeking a highly motivated Postdoctoral Researcher specializing in Explainable Artificial Intelligence (XAI) for large-scale 3D data analysis. The successful candidate will develop interpretable machine learning methods for segmentation, classification, and anomaly detection in high-dimensional volumetric datasets to support critical business and engineering decisions.\nThis role is ideal for a recent Ph.D. graduate with expertise in XAI and deep learning applied to complex spatial data. The candidate will work closely with domain experts to create transparent, trustworthy AI systems that provide actionable insights for high-stakes applications.\nKey Responsibilities\nKey Responsibilities\nDevelop explainable AI methods for deep learning models applied to 3D volumetric data.\nDesign and implement models for segmentation, classification, and anomaly detection in large-scale datasets.\nCreate techniques to improve model interpretability, transparency, and trustworthiness, including post hoc explanation and inherently interpretable approaches.\nDevelop uncertainty-aware predictions to support decision-making in critical applications.\nOptimize models for scalability and performance on large 3D datasets.\nEvaluate models using both predictive accuracy and explainability metrics relevant to domain needs.\nCollaborate with domain experts to translate model outputs into decision-support tools.\nImplement workflows using modern ML frameworks and reproducible software practices.\nCommunicate findings through technical reports, journal publications, and conference presentations.\nExample Research & Application Areas\nExplainable AI methods for deep neural networks\n3D computer vision and volumetric data analysis\nSemantic and instance segmentation in large 3D volumes\nAnomaly detection in high-dimensional spatial data\nInterpretable representations for classification models\nUncertainty quantification and confidence estimation in AI models\nHuman-in-the-loop AI and decision-support systems\nApplications to subsurface imaging, industrial inspection, and sensor data\nRequired Qualifications\nPh.D. in Computer Science, Artificial Intelligence, Machine Learning, Computational Science, or a closely related field, with a focus on explainable AI or interpretable machine learning.\nDemonstrated research experience in explainable AI and deep learning, including one or more of:Model interpretability (e.g., saliency methods, attribution, feature importance)\nExplainability techniques for neural networks\nInterpretable model design\n\nExperience with 3D data (e.g., volumetric imaging, point clouds, or spatiotemporal data) and deep learning methods such as CNNs, transformers, or graph neural networks.\nProven experience in segmentation, classification, or anomaly detection tasks.\nStrong programming skills in Python.\nHands-on experience with machine learning frameworks such as PyTorch or TensorFlow.\nStrong analytical, problem-solving, and communication skills.\nAbility to work effectively in multidisciplinary teams.\nPreferred Qualifications\nExperience with XAI methods for computer vision or 3D data.\nFamiliarity with uncertainty quantification, probabilistic ML, or Bayesian deep learning.\nExperience with large-scale data processing and GPU-accelerated training.\nKnowledge of evaluation metrics for explainability and model trustworthiness.\nExperience applying AI to engineering, geospatial, industrial, or scientific datasets.\nStrong publication record in XAI, machine learning, or computer vision.\nDemonstrated ability to translate research into decision-support applications.\nDesired Attributes\nPassion for developing trustworthy and interpretable AI systems.\nInterest in solving high-impact, real-world problems involving complex data.\nAbility to bridge machine learning methods with practical decision-making needs.\nCollaborative mindset and strong communication skills.\nSelf-driven with the ability to independently lead research initiatives.\nDuration\nThis opportunity is for a postdoctoral position expected to last one to three years, subject to annual review and renewal.\nWork Location\nThis post doctoral research position will be located at our main corporate office in Spring, Texas.\nYour Total Rewards\nAn ExxonMobil career is one designed to last. Our commitment to you runs deep: our employees grow personally and professionally, with benefits built on our core categories of health, security, finance, and life. Individual pay is determined based on various factors including degree/education, discipline, year of study, skills, abilities, qualifications, and work experience.\nMore information on our Company’s benefits can be found at www.exxonmobilfamily.com.\nPlease note pay rates and benefits may be changed from time to time without notice, subject to applicable law.\nRelocation Options\nRelocation benefits may be available to you based on ExxonMobil eligibility guidelines.\nEqual Opportunity Employer\nExxonMobil is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, sexual orientation, gender identity, national origin, citizenship status, protected veteran status, genetic information, or physical or mental disability.\nNothing herein is intended to override the corporate separateness of local entities. Working relationships discussed herein do not necessarily represent a reporting connection, but may reflect a functional guidance, stewardship, or service relationship.\nExxon Mobil Corporation has numerous affiliates, many with names that include ExxonMobil, Exxon, Esso and Mobil. For convenience and simplicity, those terms and terms like corporation, company, our, we and its are sometimes used as abbreviated references to specific affiliates or affiliate groups. Abbreviated references describing global or regional operational organizations and global or regional business lines are also sometimes used for convenience and simplicity. Similarly, ExxonMobil has business relationships with thousands of customers, suppliers, governments, and others. For convenience and simplicity, words like venture, joint venture, partnership, co-venturer, and partner are used to indicate business relationships involving common activities and interests, and those words may not indicate precise legal relationships.","description_format":"text","description_chars":7562,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"phd","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":true,"industries":["Artificial Intelligence","Energy & Utilities","Natural Resources","Fossil Fuels"],"lifecycle":[{"event":"open","at":"2026-09-30T00:57:55Z"}],"visa":[],"liveness":{"score":9,"band":"cold","label":"Long shot","p_open":1,"p_active":0.335,"p_room":0.28,"age_days":72,"expected_fill_days":30,"reasons":["conf:13","velocity","win:tail","crowd:brand"],"computed_at":"2026-10-26T05:57:25Z"},"pay":null,"html_url":"https://alion.io/job/exxonmobil-postdoctoral-researcher-explainable-ai-for-3d-data","json_url":"https://alion.io/job/exxonmobil-postdoctoral-researcher-explainable-ai-for-3d-data.json","meta":{"generated_at":"2026-10-26T06:55:31Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":9216,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-27T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":15984},"rest":"https://alion.io/mcp/rest/get_company?id=15984"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fexxonmobil-postdoctoral-researcher-explainable-ai-for-3d-data"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fexxonmobil-postdoctoral-researcher-explainable-ai-for-3d-data"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fexxonmobil-postdoctoral-researcher-explainable-ai-for-3d-data"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/exxonmobil-postdoctoral-researcher-explainable-ai-for-3d-data\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fexxonmobil-postdoctoral-researcher-explainable-ai-for-3d-data"}]}