Postdoc for AI/ML Accelerated Nanomaterial Modeling in Upton, NY, for Brookhaven National Laboratory

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Please wait.</span> </div> </div> </div> <div class="bti-job-search-results" data-result-count="2074"> <div class="card position-relative"> <div id="bti-job-21105582" class="card-body bti-job-search-row bti-job-results-highlighted" data-job-path="/jobs/21105582/postdoc-for-ai-ml-accelerated-nanomaterial-modeling" data-job="21105582"> <div class="bti-grid-search-row no-gutters"> <div class="bti-grid-sidenav text-center"> <div class="card-img-holder"> <img class='img-fluid' itemprop='URL' src="/nsutilities/showLogo.cfm?id=B36EED95-FCEA-12B5-EBAE-1B4D3AAAF14D&orgType=employer&logoType=Primary" border="0" id="bti-Primary-B36EED95-FCEA-12B5-EBAE-1B4D3AAAF14D" alt="Brookhaven National Laboratory Logo"> </div> </div> <div class="bti-grid-search-contentarea"> <div class="card-title"><a href="/jobs/21105582/postdoc-for-ai-ml-accelerated-nanomaterial-modeling">Postdoc for AI/ML Accelerated Nanomaterial Modeling</a></div> <div class="card-subtitle"> Brookhaven National Laboratory </div> <p class="card-text"> Upton, NY, </p> </div> </div> <div class="bti-search-grid-row"> <div class="bti-grid-search-col text-end"> <span class="bti-badge bg-success">NEW! 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Please wait.</span> </div> </div> <div class="bti-job-detail-pane" id="bti-search-detail"> <script type="application/ld+json"> {"@context":"http://schema.org","baseSalary":{"currency":"USD","@type":"MonetaryAmount","value":{"unitText":"Unknown","@type":"QuantitativeValue","value":"Commensurate with experience."}},"industry":["Biotechnology"],"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Upton, NY","addressCountry":"USA"}},"educationRequirements":"","url":"https://main.hercjobs.org/jobs/21105582/postdoc-for-ai-ml-accelerated-nanomaterial-modeling","employmentType":"FULL_TIME","image":"https://main.hercjobs.org/nsutilities/showLogo.cfm?id=714966&orgType=employer&logoType=Primary","hiringOrganization":{"@type":"Organization","id":"http://www.bnl.gov","url":"http://www.bnl.gov","name":"Brookhaven National Laboratory"},"description":"<p> <b> Brookhaven National Laboratory is committed to employee success and we believe that a comprehensive employee benefits program is an important and meaningful part of the compensation employees receive. Review more information at <a href=\"/externalLink.cfm?link=https%3A%2F%2Fwww%2Ebnl%2Egov%2Fhr%2Fbenefits%2F\">BNL | Benefits Program</a> </b> </p> <p /> <u>Organization Overview:</u> <p> <br /> The Center for Functional Nanomaterials (CFN) at Brookhaven is a DOE-funded national scientific user facility, offering users a supported research experience with top-caliber scientists and access to state-of-the- art instrumentation. The CFN mission is advancing nanoscience through frontier fundamental research and technique development and is the nexus of a broad collaboration network. Each year, CFN staff members support the research of nearly 600 external facility users. </p> <p> <br /> Three strategic nanoscience themes underlie the CFN scientific facilities: The CFN conducts research on nanomaterial synthesis by assembly designing precise architectures with targeted functionality by organizing nanoscale components. The CFN researches and applies platforms for state-of-the-art techniques for Accelerated Nanomaterial Discovery, integrating synthesis, advanced characterization, physical modeling, and computer science to iteratively explore a wide range of material parameters. The CFN develops and utilizes advanced capabilities for studies of Nanomaterials in Operando Conditions for characterizing materials and reactions at the atomic scale in real-world environments. </p> <br /> <u>Position Description:</u> <p /> <p>In this position, you will be a member of the Theory and Computation group working under the supervision of Sara Mason. You will play a key role in advancing the development of machine-learned interatomic potentials (MLIPs) for nanomaterials and applying them to model complex systems. Your work will involve close collaboration with scientists specializing in areas such as energy storage, catalysis, and geochemistry. You will investigate ultra-long timescale reaction dynamics using advanced quantum mechanical calculations, MLIPs, and problem-specific AI/ML approaches. This position offers the opportunity to work in an interdisciplinary team and contribute to cutting-edge research at the intersection of nanoscience and machine learning.</p> <p /> <u>Essential Duties and Responsibilities:</u> <ul> <li> <p>You will perform molecular dynamics simulations using MILPs.</p> </li> <li> <p>You will perform density functional theory (DFT) calculations for solid state materials.</p> </li> <li> <p>You will build and train machine learning models to enhance materials research.</p> </li> <li> <p>You will model the stability and transformations of nanomaterials under different conditions.</p> </li> <li> <p>You will disseminate your results through publications and conference presentations.</p> </li> </ul> <p /> <u>Required Knowledge, Skills, and Abilities:</u> <ul> <li> <p>You are committed to fostering an environment of safe scientific work practices</p> </li> <li> <p>You have earned a Ph.D. in chemistry, materials science, physics or a related discipline within the past five years and will complete your degree prior to the start date.</p> </li> <li> <p>You have experience with density functional theory or molecular dynamics simulations.</p> </li> <li> <p>You have experience in programming, particularly using Python.</p> </li> <li> <p>Your research experience is demonstrated through publications, conference records, GitHub repository records, or other public communications.</p> </li> </ul> <p /> <u>Preferred Knowledge, Skills, and Abilities:</u> <ul> <li> <p>You have experience developing and applying machine learning models</p> </li> <li> <p>You have experience in ab initio molecular dynamics.</p> </li> <li> <p>You are familiar with CUDA programming and GPU-based computing.</p> </li> <li> <p>You have experience with machine learning frameworks such as Pytorch or TensorFlow.</p> </li> <li> <p>You communicate effectively, both verbally and through technical writing.</p> </li> </ul> <p /> <u>Other Information:</u> <ul> <li> <p>This is a 2-year Postdoc Assignment.</p> </li> <li> <p>BNL policy requires that after obtaining a PhD, eligible candidates for research associate appointments may not exceed a combined total of 5 years of relevant work experience as a post- doc and/or in an R&D position, excluding time associated with family planning, military service, illness, or other life-changing events.</p> </li> <li> <p>Candidates must have completed all degree requirements by the commencement of the employment.</p> </li> </ul> <p /> <p>Brookhaven National Laboratory is committed to providing fair, equitable and competitive compensation. The full salary range for this position is $71900 - $80000/ year. Salary offers will be commensurate with the final candidate's qualification, education and experience and considered with the internal peer group.</p> <p> <b> <u>About Us</u> </b> </p> <p> Brookhaven National Laboratory (www.bnl.gov) delivers discovery science and transformative technology to power and secure the nation's future. Brookhaven Lab is a multidisciplinary laboratory with seven Nobel Prize-winning discoveries, 37 R&D 100 Awards, and more than 70 years of pioneering research. The Lab is primarily supported by the U.S. Department of Energy's (DOE) Office of Science. Brookhaven Science Associates (BSA) operates and manages the Laboratory for DOE. BSA is a partnership between Battelle and The Research Foundation for the State University of New York on behalf of Stony Brook University. BSA salutes our veterans and active military members with careers that leverage the skills and unique experience they gained while serving our country, learn more at <a href=\"/externalLink.cfm?link=https%3A%2F%2Fwww%2Ebnl%2Egov%2Fhr%2Fcareers%2Fveterans%2F\">BNL | Opportunities for Veterans at Brookhaven National Laboratory</a> . </p> <p /> <p> <b> <u>Equal Opportunity/Affirmative Action Employer</u> </b> </p> <p /> <p>Brookhaven Science Associates is an equal opportunity employer that values inclusion and diversity at our Lab. We are committed to ensuring that all qualified applicants receive consideration for employment and will not be discriminated against on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, status as a veteran, disability or any other federal, state or local protected class. BSA takes affirmative action in support of its policy and to advance in employment individuals who are minorities, women, protected veterans, and individuals with disabilities. We ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation. *VEVRAA Federal Contractor</p> <p /> <p> BSA employees are subject to restrictions related to participation in Foreign Government Talent Recruitment Programs, as defined and detailed in United States Department of Energy Order 486.1A. You will be asked to disclose any such participation at the time of hire for review by Brookhaven. 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Review more information at <a target="_blank" href="https://www.bnl.gov/hr/benefits/" rel="nofollow">BNL | Benefits Program</a></span></b></p><p></p><h2></h2><h2><u>Organization Overview:</u></h2><p><br>The Center for Functional Nanomaterials (CFN) at Brookhaven is a DOE-funded national scientific user facility, offering users a supported research experience with top-caliber scientists and access to state-of-the- art instrumentation. The CFN mission is advancing nanoscience through frontier fundamental research and technique development and is the nexus of a broad collaboration network. Each year, CFN staff members support the research of nearly 600 external facility users.</p><p><br>Three strategic nanoscience themes underlie the CFN scientific facilities: The CFN conducts research on nanomaterial synthesis by assembly designing precise architectures with targeted functionality by organizing nanoscale components. The CFN researches and applies platforms for state-of-the-art techniques for Accelerated Nanomaterial Discovery, integrating synthesis, advanced characterization, physical modeling, and computer science to iteratively explore a wide range of material parameters. The CFN develops and utilizes advanced capabilities for studies of Nanomaterials in Operando Conditions for characterizing materials and reactions at the atomic scale in real-world environments.</p><h2><br><u>Position Description:</u></h2><p></p><p>In this position, you will be a member of the Theory and Computation group working under the supervision of Sara Mason. You will play a key role in advancing the development of machine-learned interatomic potentials (MLIPs) for nanomaterials and applying them to model complex systems. Your work will involve close collaboration with scientists specializing in areas such as energy storage, catalysis, and geochemistry. You will investigate ultra-long timescale reaction dynamics using advanced quantum mechanical calculations, MLIPs, and problem-specific AI/ML approaches. This position offers the opportunity to work in an interdisciplinary team and contribute to cutting-edge research at the intersection of nanoscience and machine learning.</p><p></p><h2><u>Essential Duties and Responsibilities:</u></h2><ul><li><p>You will perform molecular dynamics simulations using MILPs.</p></li><li><p>You will perform density functional theory (DFT) calculations for solid state materials.</p></li><li><p>You will build and train machine learning models to enhance materials research.</p></li><li><p>You will model the stability and transformations of nanomaterials under different conditions.</p></li><li><p>You will disseminate your results through publications and conference presentations.</p></li></ul><p></p><h2><u>Required Knowledge, Skills, and Abilities:</u></h2><ul><li><p>You are committed to fostering an environment of safe scientific work practices</p></li><li><p>You have earned a Ph.D. in chemistry, materials science, physics or a related discipline within the past five years and will complete your degree prior to the start date.</p></li><li><p>You have experience with density functional theory or molecular dynamics simulations.</p></li><li><p>You have experience in programming, particularly using Python.</p></li><li><p>Your research experience is demonstrated through publications, conference records, GitHub repository records, or other public communications.</p></li></ul><p></p><h2><u>Preferred Knowledge, Skills, and Abilities:</u></h2><ul><li><p>You have experience developing and applying machine learning models</p></li><li><p>You have experience in ab initio molecular dynamics.</p></li><li><p>You are familiar with CUDA programming and GPU-based computing.</p></li><li><p>You have experience with machine learning frameworks such as Pytorch or TensorFlow.</p></li><li><p>You communicate effectively, both verbally and through technical writing.</p></li></ul><p></p><h2><u>Other Information:</u></h2><ul><li><p>This is a 2-year Postdoc Assignment.</p></li><li><p>BNL policy requires that after obtaining a PhD, eligible candidates for research associate appointments may not exceed a combined total of 5 years of relevant work experience as a post- doc and/or in an R&D position, excluding time associated with family planning, military service, illness, or other life-changing events.</p></li><li><p>Candidates must have completed all degree requirements by the commencement of the employment.</p></li></ul><p></p><p>Brookhaven National Laboratory is committed to providing fair, equitable and competitive compensation. The full salary range for this position is $71900 - $80000/ year. Salary offers will be commensurate with the final candidate's qualification, education and experience and considered with the internal peer group.</p><p><b><u>About Us</u></b></p><p>Brookhaven National Laboratory (www.bnl.gov) delivers discovery science and transformative technology to power and secure the nation's future. Brookhaven Lab is a multidisciplinary laboratory with seven Nobel Prize-winning discoveries, 37 R&D 100 Awards, and more than 70 years of pioneering research. The Lab is primarily supported by the U.S. Department of Energy's (DOE) Office of Science. Brookhaven Science Associates (BSA) operates and manages the Laboratory for DOE. BSA is a partnership between Battelle and The Research Foundation for the State University of New York on behalf of Stony Brook University. BSA salutes our veterans and active military members with careers that leverage the skills and unique experience they gained while serving our country, learn more at <a href="https://www.bnl.gov/hr/careers/veterans/" target="_blank" rel="nofollow">BNL | Opportunities for Veterans at Brookhaven National Laboratory</a>.</p><p></p><p><b><u>Equal <span><span><span><span>Opportunity/Affirmative</span></span></span></span> Action Employer</u></b></p><p></p><p>Brookhaven Science Associates is an equal opportunity employer that values inclusion and diversity at our Lab. We are committed to ensuring that all qualified applicants receive consideration for employment and will not be discriminated against on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, status as a veteran, disability or any other federal, state or local protected class. BSA takes affirmative action in support of its policy and to advance in employment individuals who are minorities, women, protected veterans, and individuals with disabilities. We ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation. *VEVRAA Federal Contractor</p><p></p><p>BSA employees are subject to restrictions related to participation in Foreign Government Talent Recruitment Programs, as defined and detailed in United States Department of Energy Order 486.1A. You will be asked to disclose any such participation at the time of hire for review by Brookhaven. 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Postdoc for AI/ML Accelerated Nanomaterial Modeling in Upton, NY, for Brookhaven National Laboratory