UF
Scientist [181815]
Accepting applicationsU.S. Fusion Energy · Laskein, Meghalaya, India
Full-Time Mid AIC++DFT
Estimated market salary
₹9-14 LPA
This is a SiliconBoard market estimate, not an employer-posted salary.
Posted
20h ago
Category
Test
Experience
Mid
Country
India
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Scientist
University of Rochester: Office of the Provost: Academic Center: LLE-Laboratory for Laser Energ
Location
Laboratory for Laser Energetics
Open Date
Apr 15, 2026
Salary Range or Pay Grade
$100,000-$140,000 Annually
Description
POSITION SUMMARY:
The High-Energy-Density Physics Theory Group at LLE is seeking an outstanding computational and theoretical scientist to conduct rigorous, high-impact research in high-energy-density (HED) science relevant to inertial confinement fusion (ICF), the Stockpile Stewardship Program (SSP), and fundamental science. The successful candidate will make significant contributions to ongoing efforts to develop (i) the finite-element, mixed deterministic–stochastic density functional theory (DFT) code MELIORA and (ii) LLE’s next-generation opacity code for HED plasmas, ROCSTAR. Candidates must have strong experience in computational physics and experimental modeling, as well as solid programming skills in C++ and/or Fortran 90. The ideal candidate will have expertise in one or more of the following areas: computational physics, condensed matter physics, quantum chemistry, plasma physics, materials science, and/or atomic and molecular physics.
Responsiblities
Take a leading role in developing LLE’s DFT code MELIORA using modern software engineering, coding, and testing practices
Enable MELIORA for efficient and accurate quantum molecular dynamics (QMD) simulations of dynamical materials over a wide range of densities and temperatures
Develop time-dependent density functional theory (TDDFT) capabilities in MELIORA and apply them to study dynamical properties of HED materials
Assist in the development of LLE’s next-generation opacity code ROCSTAR for HED plasmas
Perform ROCSTAR calculations and validation against benchmarking experiments
Collaborate with experimentalists at LLE and partner institutions to benchmark MELIORA and ROCSTAR against high-precision HED experimental data
Publish research results in high-impact, peer-reviewed journals
Advise graduate and undergraduate students conducting computational HED physics research
Qualifications
MINIMUM EDUCATION & EXPERIENCE:
PhD degree in computational physics, condensed matter physics, quantum chemistry, plasma physics, materials science, or atomic and molecular physics
Demonstrated proficiency in C++ and/or Fortran 90 for scientific computing
At least five years of research experience in computational sciences, including a minimum of two years of postdoctoral experience at national laboratories or universities
Strong written and oral communication skills
Ability to work effectively both independently and as part of a multidisciplinary team
Application Instructions
The Applicant Should Submit
a cover letter;
a curriculum vitae and a list of publications;
at least two letters of recommendation
SALARY RANGE: $100,000 to $140,000
The referenced pay range represents the minimum and maximum compensation for this job. Individual annual salaries/hourly rates are set within the job's compensation range, and determined by considering factors including, but not limited to, market data, education, experience, qualifications, expertise of the individual, and internal equity considerations.
Application Process
This institution is using Interfolio's Faculty Search to conduct this search. Applicants to this position receive a free Dossier account and can send all application materials, including confidential letters of recommendation, free of charge.
Apply Now
Equal Employment Opportunity Statement
EOE, including disability/protected veterans
The University of Rochester is committed to fostering, cultivating, and preserving an inclusive and welcoming culture to advance the University’s Mission to Learn, Discover, Heal, Create – and Make the World Ever Better. In support of our values and those of our society, the University is committed to not discriminating on the basis of age, color, disability, ethnicity, gender identity or expression, genetic information, marital status, military/veteran status, national origin, race, religion/creed, sex, sexual orientation, citizenship status, or any other characteristic protected by federal, state, or local law (Protected Classes). This commitment extends to non-discrimination in the administration of our policies, admissions, employment, access, and recruitment of candidates for all persons consistent with our values and based on applicable law.
© 2026 Elsevier Inc. or its licensors and contributors. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
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Scientist
University of Rochester: Office of the Provost: Academic Center: LLE-Laboratory for Laser Energ
Location
Laboratory for Laser Energetics
Open Date
Apr 15, 2026
Salary Range or Pay Grade
$100,000-$140,000 Annually
Description
POSITION SUMMARY:
The High-Energy-Density Physics Theory Group at LLE is seeking an outstanding computational and theoretical scientist to conduct rigorous, high-impact research in high-energy-density (HED) science relevant to inertial confinement fusion (ICF), the Stockpile Stewardship Program (SSP), and fundamental science. The successful candidate will make significant contributions to ongoing efforts to develop (i) the finite-element, mixed deterministic–stochastic density functional theory (DFT) code MELIORA and (ii) LLE’s next-generation opacity code for HED plasmas, ROCSTAR. Candidates must have strong experience in computational physics and experimental modeling, as well as solid programming skills in C++ and/or Fortran 90. The ideal candidate will have expertise in one or more of the following areas: computational physics, condensed matter physics, quantum chemistry, plasma physics, materials science, and/or atomic and molecular physics.
Responsiblities
Take a leading role in developing LLE’s DFT code MELIORA using modern software engineering, coding, and testing practices
Enable MELIORA for efficient and accurate quantum molecular dynamics (QMD) simulations of dynamical materials over a wide range of densities and temperatures
Develop time-dependent density functional theory (TDDFT) capabilities in MELIORA and apply them to study dynamical properties of HED materials
Assist in the development of LLE’s next-generation opacity code ROCSTAR for HED plasmas
Perform ROCSTAR calculations and validation against benchmarking experiments
Collaborate with experimentalists at LLE and partner institutions to benchmark MELIORA and ROCSTAR against high-precision HED experimental data
Publish research results in high-impact, peer-reviewed journals
Advise graduate and undergraduate students conducting computational HED physics research
Qualifications
MINIMUM EDUCATION & EXPERIENCE:
PhD degree in computational physics, condensed matter physics, quantum chemistry, plasma physics, materials science, or atomic and molecular physics
Demonstrated proficiency in C++ and/or Fortran 90 for scientific computing
At least five years of research experience in computational sciences, including a minimum of two years of postdoctoral experience at national laboratories or universities
Strong written and oral communication skills
Ability to work effectively both independently and as part of a multidisciplinary team
Application Instructions
The Applicant Should Submit
a cover letter;
a curriculum vitae and a list of publications;
at least two letters of recommendation
SALARY RANGE: $100,000 to $140,000
The referenced pay range represents the minimum and maximum compensation for this job. Individual annual salaries/hourly rates are set within the job's compensation range, and determined by considering factors including, but not limited to, market data, education, experience, qualifications, expertise of the individual, and internal equity considerations.
Application Process
This institution is using Interfolio's Faculty Search to conduct this search. Applicants to this position receive a free Dossier account and can send all application materials, including confidential letters of recommendation, free of charge.
Apply Now
Equal Employment Opportunity Statement
EOE, including disability/protected veterans
The University of Rochester is committed to fostering, cultivating, and preserving an inclusive and welcoming culture to advance the University’s Mission to Learn, Discover, Heal, Create – and Make the World Ever Better. In support of our values and those of our society, the University is committed to not discriminating on the basis of age, color, disability, ethnicity, gender identity or expression, genetic information, marital status, military/veteran status, national origin, race, religion/creed, sex, sexual orientation, citizenship status, or any other characteristic protected by federal, state, or local law (Protected Classes). This commitment extends to non-discrimination in the administration of our policies, admissions, employment, access, and recruitment of candidates for all persons consistent with our values and based on applicable law.
© 2026 Elsevier Inc. or its licensors and contributors. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
Support|Careers|Accessibility Policy|Cookies Settings|Privacy Policy|Terms of Service
We use cookies that are necessary to make our site work. We may also use additional cookies to analyze, improve, and personalize our content and your digital experience. You can manage your cookie preferences using theCookie settings link. For more information, see ourCookie Policy
Opt-Out Request Honored
Cookie Preference Center
We use cookies which are necessary to make our site work. We may also use additional cookies to analyse, improve and personalise our content and your digital experience. For more information, see our Cookie Policy and the list of Google Ad-Tech Vendors.
You may choose not to allow some types of cookies. However, blocking some types may impact your experience of our site and the services we are able to offer. See the different category headings below to find out more or change your settings.
You may also be able to exercise your privacy choices as described in our Privacy Policy
Manage Consent Preferences
Strictly Necessary Cookies
Always active
These cookies are necessary for the website to function and cannot be switched off in our systems. They are usually only set in response to actions made by you which amount to a request for services, such as setting your privacy preferences, logging in or filling in forms. You can set your browser to block or alert you about these cookies, but some parts of the site will not then work.
Functional Cookies
Functional Cookies
These cookies enable the website to provide enhanced functionality and personalisation. They may be set by us or by third party providers whose services we have added to our pages. If you do not allow these cookies then some or all of these services may not function properly.
Performance Cookies
Performance Cookies
These cookies allow us to count visits and traffic sources so we can measure and improve the performance of our site. They help us to know which pages are the most and least popular and see how visitors move around the site.
Targeting Cookies
Targeting Cookies
These cookies may be set through our site by our advertising partners. They may be used by those companies to build a profile of your interests and show you relevant adverts on other sites. If you do not allow these cookies, you will experience less targeted advertising.
Cookie List
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