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Lead Software Developer - GPU-accelerated Free Energy Simulation and Machine Learning Methods

Piscataway, NJ, US • Posted 5 hours ago • Updated 5 hours ago

Full Time

On-site

USD 93,588.00 per year

Fitment

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Job Details

Skills

Taxes
Life Insurance
Research
Biomedicine
Jersey
Management
Artificial Intelligence
Mechanical Engineering
Biology
Chemistry
Object-Oriented Programming
Python
C++
CUDA
Software Engineering
Training
Machine Learning (ML)
High Performance Computing
Communication
English
Laptop
Virtual Team
Reporting
GPU
Energy
Deep Learning
Software Development
Documentation
Workflow
Art
Recruiting
Partnership
Collaboration
Military
Cellular
Testing
Law

Taxes
Life Insurance
Research
Biomedicine
Jersey
Management
Artificial Intelligence
Mechanical Engineering
Biology
Chemistry
Object-Oriented Programming
Python
C++
CUDA
Software Engineering
Training
Machine Learning (ML)
High Performance Computing
Communication
English
Laptop
Virtual Team
Reporting
GPU
Energy
Deep Learning
Software Development
Documentation
Workflow
Art
Recruiting
Partnership
Collaboration
Military
Cellular
Testing
Law

Summary

Position Details

Position Information

Recruitment/Posting Title
Lead Software Developer - GPU-accelerated Free Energy Simulation and Machine Learning Methods

Department
Quantitative Biomedicine Inst

Salary Details
$93,588 Minimum

Offer Information

The final salary offer may be determined by several factors, including, but not limited to, the candidate's qualifications, experience, and expertise, and availability of department or grant funds to support the position. We also take into consideration market benchmarks, if and when appropriate, and internal equity to ensure fair compensation relative to the university's broader compensation structure. We are committed to offering competitive and flexible compensation packages to attract and retain top talent.

Benefits

Rutgers provides a comprehensive benefits package to eligible employees. The specific benefits vary based on the position and may include:

Medical, prescription drug, and dental coverage
Paid vacation, holidays, and various leave programs
Competitive retirement benefits, including defined contribution plans and voluntary tax-deferred savings options
Employee and dependent educational benefits (when applicable)
Life insurance coverage
Employee discount programs

Posting Summary

The Laboratory for Biomolecular Simulation Research (;/strong>) and Institute for Quantitative Biomedicine (;/strong>) at Rutgers, the State University of New Jersey, is seeking a high-level software development scientist to create new modern free energy simulation and quantum mechanical/artificial intelligence tools. At Rutgers, the LBSR is directed by Professor Darrin York, and is dedicated to the development and application of innovative biomolecular simulation tools for enzyme design and drug discovery (;/strong>). The successful candidate will develop new GPU-accelerated software for alchemical free energy and new AI-enhanced quantum mechanical force fields built using integrated semiempirical density-functional tight-binding and deep-learning neural networks. These methods will be integrated into the next-generation Amber software suite used worldwide. The project is to design and implement new high-performance software for drug discovery. The successful candidate will work in close contact with Amber developers to implement new methods and optimize code useability and performance that leverages the latest GPU technology. This is thus an outstanding opportunity for an ambitious scientist to be involved as a lead in a project of this scope and impact and is ideally suited for individuals with career aspirations to lead efforts in drug discovery or related new start-up company efforts.

Position Status
Full Time

Posting Number
26FA0635

Posting Open Date
06/26/2026

Posting Close Date
08/31/2026

Qualifications

Minimum Education and Experience

Applicants must hold a PhD in biology (preferred) or chemistry and have postdoctoral experience working with and developing workflows using Amber.

Certifications/Licenses

Required Knowledge, Skills, and Abilities

This is a high-level software development position that requires proficiency in object-oriented programming (particularly python and C++, and GPU programming, e.g., cuda) and experience in software engineering and design. In addition, training in the use of molecular simulation methods is requisite, particularly alchemical free energy and/or quantum/machine-learning methods, as well as high-performance computing. Deep familiarity with free energy workflows and Amber is essential. Strong written and oral communication skills in English are required, as well as the ability to work independently and prepare scientific manuscripts and/or proposals.

Preferred Qualifications

Equipment Utilized

Software development will involve computer resources at Rutgers and include access to in-house and national production cyberinfrastructure resources.

Physical Demands and Work Environment

Predominantly operates in an office environment using computer workstation and/or laptop computer, participates in both physical and virtual team meetings, and periodically attends workshops and/or conferences that entail domestic or international travel. Remote work, with regularly scheduled in-person reporting to the PI, is possible through mutual agreement.

Overview

Applicant is expected to develop software for GPU-accelerated alchemical free energy and quantum/deep-learning potential simulations. Duties will involve software development, testing and documentation, applications within drug discovery workflows including performing simulations of relative and absolute ligand-protein binding, analysis of thermodynamic graphs, maintaining currency in the relevant literature and state-of-the-art technology, and actively engage in a team environment.

Statement

Posting Details

Special Instructions to Applicants

Quick Link to Posting
;br>
Campus
Rutgers University-New Brunswick

Home Location Campus
Busch (RU-New Brunswick)

City
Piscataway

State
NJ

Location Details

Pre-employment Screenings

All offers of employment are contingent upon successful completion of all pre-employment screenings.

Immunization Requirements
Under Policy 100.3.1 Immunization Policy for Covered Individuals, if employment will commence during Flu Season, Rutgers University may require certain prospective employees to provide proof that they are vaccinated against Seasonal Influenza for the current Flu Season, unless the University has granted the individual a medical or religious exemption. Additional infection control and safety policies may apply. Prospective employees should speak with their hiring manager to determine which policies apply to the role or position for which they are applying. Failure to provide proof of vaccination for any required vaccines or obtain a medical or religious exemption from the University will result in rescission of a candidate's offer of employment or disciplinary action up to and including termination.

Equal Employment Opportunity Statement

It is university policy to provide equal employment opportunity to all its employees and applicants for employment regardless of their race, creed, color, national origin, age, ancestry, nationality, marital or domestic partnership or civil union status, sex, pregnancy, gender identity or expression, disability status, liability for military service, protected veteran status, affectional or sexual orientation, atypical cellular or blood trait, genetic information (including the refusal to submit to genetic testing), or any other category protected by law. As an institution, we encourage all qualified applicants to apply. For additional information please see the Non-Discrimination Statement at the following web address:

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
Dice Id: 10105064
Position Id: 9363a82f726b3f8f3b44c14173a6223a
Posted 5 hours ago

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