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Molecular Dynamics Simulation Protein Jobs in Silver Spring, MD

Varsity Tutors

AP Biology Tutor

Rockville, MD · Remote

$18 - $40/hr

Emphasizes scientific practices and connects molecular biology to ecology, medicine, and ... Adapts instruction using diagrams, lab simulations, and AP-style practice questions to support ...

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AP Biology Tutor

Leesburg, VA · Remote

$18 - $40/hr

Emphasizes scientific practices and connects molecular biology to ecology, medicine, and ... Adapts instruction using diagrams, lab simulations, and AP-style practice questions to support ...

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AP Biology Tutor

College Park, MD · Remote

$18 - $40/hr

Emphasizes scientific practices and connects molecular biology to ecology, medicine, and ... Adapts instruction using diagrams, lab simulations, and AP-style practice questions to support ...

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AP Biology Tutor

Washington, DC · Remote

$18 - $40/hr

Emphasizes scientific practices and connects molecular biology to ecology, medicine, and ... Adapts instruction using diagrams, lab simulations, and AP-style practice questions to support ...

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AP Biology Tutor

Alexandria, VA · Remote

$18 - $40/hr

Emphasizes scientific practices and connects molecular biology to ecology, medicine, and ... Adapts instruction using diagrams, lab simulations, and AP-style practice questions to support ...

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AP Biology Tutor

Baltimore, MD · Remote

$18 - $40/hr

Emphasizes scientific practices and connects molecular biology to ecology, medicine, and ... Adapts instruction using diagrams, lab simulations, and AP-style practice questions to support ...

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AP Biology Tutor

Laurel, MD · Remote

$18 - $40/hr

Emphasizes scientific practices and connects molecular biology to ecology, medicine, and ... Adapts instruction using diagrams, lab simulations, and AP-style practice questions to support ...

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All JobsMolecular Dynamics Simulation Protein JobsMolecular Dynamics Simulation Protein Jobs in Silver Spring, MD

Molecular Dynamics Simulation Protein information

See Silver Spring, MD salary details

$11.4K

$83.4K

$107K

How much do molecular dynamics simulation protein jobs pay per year?

As of Aug 23, 2026, the average yearly pay for molecular dynamics simulation protein in Silver Spring, MD is $83,412.00, according to ZipRecruiter salary data. Most workers in this role earn between $71,300.00 and $101,800.00 per year, depending on experience, location, and employer.

What is a molecular dynamics simulation protein?

Molecular dynamics simulation proteins refer to the use of computer simulations to study the physical movements and interactions of protein molecules over time. These simulations help scientists understand protein structure, folding, stability, and interactions with other molecules at an atomic level. By modeling the behavior of proteins in various environments, researchers can gain insights into biological processes and design new drugs or therapies. Molecular dynamics is a powerful tool in structural biology and bioinformatics, enabling the exploration of phenomena that are difficult to observe experimentally.

What are the key skills and qualifications needed to thrive as a molecular dynamics simulation protein specialist?

To thrive as a Molecular Dynamics Simulation Protein Specialist, you need a solid background in biophysics, computational chemistry, and molecular biology, often supported by an advanced degree such as a Ph.D. in a related field. Expertise in simulation software like GROMACS, AMBER, or CHARMM, along with proficiency in programming languages such as Python or C++, is typically required. Strong analytical thinking, problem-solving ability, and effective collaboration are essential soft skills for interpreting results and working within interdisciplinary research teams. These competencies are crucial for accurately modeling protein behaviors, generating actionable insights, and advancing scientific understanding in pharmaceutical and academic research environments.

What are some common challenges faced when running molecular dynamics simulations of proteins, and how can they be addressed?

One common challenge in this role is ensuring the accuracy and stability of protein simulations, as factors like force field selection, system size, and simulation timescale can significantly impact results. Balancing computational resources with scientific goals is crucial, as longer or more complex simulations require more processing power. Effective troubleshooting of simulation errors and optimizing workflows with automation tools are key skills. Collaboration with experimental biochemists and other computational scientists often helps validate findings and guide simulation design.

What is the difference between Molecular Dynamics Simulation Protein vs Computational Chemist?

AspectMolecular Dynamics Simulation ProteinComputational Chemist
Required CredentialsDegree in Biochemistry, Chemistry, or related field; knowledge of molecular modeling softwareDegree in Chemistry, Chemical Engineering, or related; strong background in computational methods
Work EnvironmentResearch labs, pharmaceutical companies, academic institutionsResearch labs, industry R&D, academia
Industry UsageBiotechnology, pharmaceuticals, academic researchPharmaceuticals, chemical industry, academia

While both roles involve computational modeling, Molecular Dynamics Simulation Protein focuses specifically on simulating protein behavior at the atomic level, whereas Computational Chemist covers a broader range of chemical systems and methods. The roles often overlap but differ in their specific applications and focus areas.

What are popular job titles related to Molecular Dynamics Simulation Protein jobs in Silver Spring, MD?

For Molecular Dynamics Simulation Protein jobs in Silver Spring, MD, the most frequently searched job titles are:

What job categories do people searching Molecular Dynamics Simulation Protein jobs in Silver Spring, MD look for?

The top searched job categories for Molecular Dynamics Simulation Protein jobs in Silver Spring, MD are:

Molecular Dynamics Simulation Protein jobs near you

AI Engineer - AI+CryoET

Howard Hughes Medical Institute (HHMI)

Ashburn, VA • On-site

Full-time

Medical, Retirement

Re-posted 8 days ago

Job description

Primary Work Address: 19700 Helix Drive, Ashburn, VA, 20147
Current HHMI Employees, click here to apply via your Workday account.
TLDR: Build AI methods for 3D particle detection and structural analysis in cryo-electron tomography data, applied to chromatin organization and synaptic molecular targets.
Please include a cover letter with your application. Describe a deep learning project you have executed, ideally involving 3D image analysis, inverse problems, or physics-informed modeling. Cryo-EM/ET and computational structural biology projects are especially relevant. Discuss results, limitations, and challenges encountered. If the project was collaborative, describe your specific contributions. Include links to relevant code repositories and your GitHub/Gitlab profile, personal website, or similar evidence.
About the role:
AI@HHMI: HHMI is investing $500 million over the next 10 years to support AI-driven projects and to embed AI systems throughout every stage of the scientific process in labs across HHMI. This role is part of the AI+CryoET project within AI@HHMI, a multi-institutional project at the intersection of cryo-electron tomography (cryoET), molecular dynamics simulation, and machine learning. The project aims to develop AI methods for mesoscale structural biology, understanding how cellular macromolecules organize into higher-order structures. You will work in a team at Janelia, with experimental and computational collaborators across the Rosen lab (UT Southwestern Medical Center/HHMI), Gouaux lab (Oregon Health and Science University/HHMI), Collepardo-Guevara lab (University of Cambridge), and Villa lab (UC San Diego/HHMI).
You will develop machine learning methods for particle detection, localization, and structural analysis in cryoET data, with two interconnected aims: (1) detecting gold nanoparticle (AuNP) probes to improve reconstruction quality and identify molecular targets; (2) identifying the arrangement and connectivity of nucleosomes in chromatin that give rise to chromosome structure in cell nuclei and biochemical reconstitutions. This involves developing supervised and self-supervised AI models based on simulated as well as annotated experimental cryoET data, informed by molecular dynamics simulations of relevant biological structures. Success in this role requires close collaboration with cryoET experts, structural biologists, and computer scientists to ensure models work in challenging real-world scenarios of a biologically not yet fully understood system.
What we provide:
  • A competitive compensation package with comprehensive health and welfare benefits.
  • A supportive team environment that promotes collaboration and knowledge sharing.
  • Access to world-class computational infrastructure, GPU-based computing environments, and unique high-quality cryoET datasets.
  • The opportunity to work directly with leading structural biologists, cryoET experimentalists, and molecular dynamics experts on a highly interdisciplinary project.
  • The opportunity to engage with world-class researchers, software engineers, and AI/ML experts, contribute to impactful science, and be part of a dynamic community committed to advancing humanity's understanding of fundamental scientific questions.
  • Amenities that enhance work-life balance, such as on-site childcare, free gyms, available on-campus housing, social and dining spaces, and convenient shuttle bus service to Janelia from the Washington, D.C. metro area.
  • Opportunity to partner with frontier AI labs on scientific applications of AI. See https://www.anthropic.com/news/anthropic-partners-with-allen-institute-and-howard-hughes-medical-institute

What you'll do:
  • Develop and evaluate deep learning models for detecting and localizing gold nanoparticles and macromolecular particles (e.g., nucleosomes, synaptic receptors) in cryoET data, and for identification of nucleosome arrangement and connectivity in chromatin.
  • Develop methods to leverage gold nanoparticle detections to improve tomogram reconstruction, addressing challenges in tilt-series alignment, deformations, and low signal-to-noise conditions.
  • Design and execute rigorous AI model training and evaluation pipelines, including proper handling of missing wedge artifacts, CTF effects, and sim-to-real transfer from MD-derived synthetic training data.
  • Identify where additional human annotation and proofreading will be most helpful and design and guide annotation efforts.
  • Contribute to scientific publications, present findings at conferences, and maintain a well-documented codebase enabling seamless reproduction and extension of results.
  • Collaborate with interdisciplinary teams across multiple institutions.

What you bring:
  • Master's or PhD in Computer Science, Applied Mathematics, Physics, Computational Chemistry, or a related field, or equivalent combination of education and experience.
  • 3+ years training and evaluating deep learning models, particularly on 3D or volumetric image data. Experience with detection, segmentation, or inverse problems in imaging is strongly preferred.
  • Strong Python skills, and proficiency in PyTorch and/or JAX. Ability to reason about neural network behavior from first principles: how architectural choices, regularization, and training procedures affect model behavior.
  • Rigorous experimental design: model comparisons, ablation studies, reproducibility.
  • Commitment to open science.
  • Experience with scalable GPU-based computing environments on Linux HPC clusters and high-throughput processing for large-scale data.
  • Excellent communication skills and keen interest in working in a truly interdisciplinary environment.

Ways to stand out:
  • Experience with cryo-EM/ET data processing, tomographic reconstruction, or related inverse problems in imaging.
  • Familiarity with molecular dynamics simulations (e.g., OpenMM, LAMMPS) and/or synthetic data generation for training ML models.
  • Experience with differentiable rendering, neural radiance fields, or analysis-by-synthesis approaches for 3D reconstruction.
  • Knowledge of cryoET software tools (IMOD, Warp, RELION, AreTomo etc.) or microscopy data formats (MRC, Zarr).
  • Experience with template matching, sub-tomogram averaging, or particle picking in cryo-EM/ET contexts.

Physical Requirements:
Remaining in a normal seated or standing position for extended periods of time; reaching and grasping by extending hand(s) or arm(s); dexterity to manipulate objects with fingers, for example using a keyboard; communication skills using the spoken word; ability to see and hear within normal parameters; ability to move about workspace. The position requires mobility, including the ability to move materials weighing up to several pounds (such as a laptop computer or tablet).
Persons with disabilities may be able to perform the essential duties of this position with reasonable accommodation. Requests for reasonable accommodation will be evaluated on an individual basis.
Please Note:
This job description sets forth the job's principal duties, responsibilities, and requirements; it should not be construed as an exhaustive statement, however. Unless they begin with the word "may," the Essential Duties and Responsibilities described above are "essential functions" of the job, as defined by the Americans with Disabilities Act.
Hiring Pay Range
AI Engineer I: $96,325.60 - $120,407.00
AI Engineer II: $123,125.60 - $153,907.00
AI Engineer III: $149,515.20 - $186,894.00
AI Engineer IV: $184,453.60 - $230,567.00
Pay Type: Salary
The posted range reflects HHMI's good faith estimate of the anticipated hiring salary range for this role at the time of posting. Actual hiring compensation is determined by a candidate's qualifications, experience, and internal equity.
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Compensation and Benefits
Our employees are compensated from a total rewards perspective in many ways for their contributions to our mission, including competitive pay, exceptional health benefits, retirement plans, time off, and a range of recognition and wellness programs. Visit our Benefits at HHMI site to learn more.
HHMI is an Equal Opportunity Employer
We use E-Verify to confirm the identity and employment eligibility of all new hires.

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