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Remote Computational Modeling Scientist Jobs (NOW HIRING)

The Pennsylvania State University

Approval of remote and hybrid work is not guaranteed regardless of work location.For additional ... The applicant must have prior experience with computational modeling and flume experiments.

Mercor

Subject Matter Expert

New York, NY · Remote

$70 - $100/hr

Remote Commitment: 40 hours/week Role Responsibilities * Guide research teams to close knowledge ... Demonstrated technical expertise in at least one domain: computational modeling, laboratory methods ...

Mat3ra

Computational Materials Scientist

Walnut Creek, CA · On-site +1

$90K - $140K/yr

Overview We look for computational materials scientists excited about bridging the gap between ... Work will focus on (1) the application of nanoscale modeling to large sets of materials, surfaces ...

Arva Intelligence

Data Engineer

Houston, TX · On-site +1

$95K - $130K/yr

Lead Modeling Scientist Location : Remote Base Salary Range: $95k - $130k General Position Description The Data Engineer is responsible for building and scaling the data and computational backbone ...

YO IT Consulting

Neuroscience QA Lead - Remote

... Science, Psychology, Neurobiology, Cognitive Psychology, Computational Neuroscience, Neurology ... modeling, neuropsychological assessment, statistics, Python/R/MATLAB, cognitive tasks, or ...

YO IT Consulting

Neuroscience QA Lead - Remote

... Science, Psychology, Neurobiology, Cognitive Psychology, Computational Neuroscience, Neurology ... modeling, neuropsychological assessment, statistics, Python/R/MATLAB, cognitive tasks, or ...

YO IT Consulting

Neuroscience QA Lead - Remote

... Science, Psychology, Neurobiology, Cognitive Psychology, Computational Neuroscience, Neurology ... modeling, neuropsychological assessment, statistics, Python/R/MATLAB, cognitive tasks, or ...

YO IT Consulting

Neuroscience QA Lead - Remote

... Science, Psychology, Neurobiology, Cognitive Psychology, Computational Neuroscience, Neurology ... modeling, neuropsychological assessment, statistics, Python/R/MATLAB, cognitive tasks, or ...

YO IT Consulting

Neuroscience QA Lead - Remote

... Science, Psychology, Neurobiology, Cognitive Psychology, Computational Neuroscience, Neurology ... modeling, neuropsychological assessment, statistics, Python/R/MATLAB, cognitive tasks, or ...

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Remote Computational Modeling Scientist information

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$50.5K

$111.3K

$137.5K

How much do remote computational modeling scientist jobs pay per year?

As of Jul 17, 2026, the average yearly pay for remote computational modeling scientist in the United States is $111,343.00, according to ZipRecruiter salary data. Most workers in this role earn between $94,500.00 and $137,000.00 per year, depending on experience, location, and employer.

What is the difference between Remote Computational Modeling Scientist vs Remote Data Scientist?

AspectRemote Computational Modeling ScientistRemote Data Scientist
Required CredentialsAdvanced degrees in computational science, physics, or related fields; programming skillsDegree in data science, statistics, or related fields; programming and analytical skills
Work EnvironmentResearch labs, tech companies, or industries requiring simulation and modelingBusiness, tech, healthcare, or finance sectors analyzing large datasets
Employer & Industry UsageResearch institutions, biotech, aerospace, and engineering firmsTech companies, finance, healthcare, marketing
Common Search & ComparisonYesNo

The Remote Computational Modeling Scientist focuses on developing and applying computational models to simulate complex systems, often requiring advanced scientific knowledge. In contrast, the Remote Data Scientist primarily analyzes large datasets to extract insights for business decisions. While both roles involve programming and data analysis, their core applications and industries differ significantly.

How does a Remote Computational Modeling Scientist typically collaborate with cross-functional teams while working off-site?

As a Remote Computational Modeling Scientist, you’ll often work closely with multidisciplinary teams, including experimental scientists, data analysts, and software engineers. Collaboration usually takes place through virtual meetings, shared project management tools, and cloud-based data repositories, ensuring seamless communication despite geographical distance. Clear documentation, proactive updates, and flexible scheduling are key to overcoming the challenges of time zone differences and remote coordination. Building strong professional relationships and maintaining transparency help facilitate effective teamwork and project success.

What is a Remote Computational Modeling Scientist?

A Remote Computational Modeling Scientist is a professional who uses advanced computer simulations and mathematical models to analyze complex systems or predict outcomes in fields such as physics, biology, chemistry, or engineering—all while working remotely. They design, develop, and implement computational models to solve scientific problems, often collaborating with research teams virtually. Their work helps organizations understand phenomena, optimize processes, and accelerate innovation without needing to be physically present in a traditional lab or office setting.

What are the key skills and qualifications needed to thrive as a Remote Computational Modeling Scientist, and why are they important?

To thrive as a Remote Computational Modeling Scientist, you need a strong background in mathematics, physics, or engineering, along with experience in computational modeling and a relevant advanced degree. Proficiency with programming languages (such as Python, MATLAB, or C++), simulation software, and version control systems is typically expected. Exceptional problem-solving abilities, self-motivation, and effective virtual communication are vital soft skills for remote collaboration and independent workflow. These competencies ensure accurate model development, efficient project delivery, and seamless teamwork across distributed environments.
What cities are hiring for Remote Computational Modeling Scientist jobs? Cities with the most Remote Computational Modeling Scientist job openings:
What are the most commonly searched types of Computational Modeling Scientist jobs? The most popular types of Computational Modeling Scientist jobs are:
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Remote Computational Modeling Scientist jobs near you
Computational Biologist

Computational Biologist

Verge Genomics

San Francisco, CA • On-site, Remote

Full-time

Re-posted 14 days ago

Job description

Who We Are
Verge is transforming drug discovery by using artificial intelligence and proprietary human data to solve the biggest driver of rising drug costs: high clinical failure rates. To achieve this, we have built one of the field's largest corpuses of multi-modal patient molecular and clinical data, sourced directly from human tissue. Our team of engineers, neuroscientists, and biologists have so far delivered two drugs to clinic, discovered 282 new targets, and signed commercial partnerships worth in excess of $1.6B with Eli Lily and AstraZeneca.
Your Mission
Reporting to the Head of Product & Engineering, and working alongside Verge's platform and computational biology teams, the Computational Biologist (AI/ML) will be responsible for defining and enabling new product offerings leveraging Verge's drug discovery engine for internal stakeholders, external partners (across both pharma and AI), and customers.
Your 12 Month Outcomes
  • Work with Verge's AI partners to deliver a best-in-class biology foundation model with Verge's proprietary datasets
  • Develop a novel approach that enables a powerful new product offering (patient stratification, biomarker discovery, etc.)
  • Deliver at least two CONVERGE-powered insights projects to pharma/biotech companies
  • Build an internal agentic AI workflow that supports multi-modal biomedical reasoning and orchestration

You Will
  • Develop and evaluate cutting-edge computational methodologies integrating multi-omic datasets to develop predictive models for translational biology,
  • Lead high-impact projects that apply and adapt AI models to translational challenges in disease biology, biomarker discovery, and target exploration,
  • Lead partnerships with AI companies to co-develop next-generation foundation models for drug discovery
  • Frame biological problems in computational terms and design solutions that are biologically meaningful, interpretable, and experimentally testable,
  • Design and implement evaluation methodologies for assessing AI model capabilities relevant to biological research and applications,
  • Translate between biological domain knowledge and machine learning objectives.

Requirements
Candidates must have:
  • Either:
    • PhD in computational biology, AI/ML, applied statistics, biophysics, or,
    • MS and professional experience in relevant fields.
  • ≥5 years of experience working in applied computational biology and integration of multi-omic datasets (RNA-seq, genotyping, clinical), with ≥2 years in a startup environment,
  • ≥2 years of experience in relevant areas of translational science, demonstrating a deep understanding of target identification, biomarker discovery, and/or patient stratification,
  • Proven ability to implement, evaluate, and/or create computational methodologies that leverage machine learning, statistics, and AI for biological research and discovery,
  • Fluency with state of the art in systems biology workflows, including off-the-shelf biological databases and computational biology tools,
  • Track record of bridging biological domain knowledge with computational approaches to solve real scientific problems
  • Track record of individual innovation, with published research or shipped work influencing pharma R&D decisions
  • Experience running a significant number of end-to-end RNA-Seq data analyses (from QC, read quantification, normalization through to interpretation),
  • Excellent coding skills in Python, with experience in relevant ML/AI libraries (e.g., PyTorch, HuggingFace, scikit-learn, pandas, numpy). A demonstrable portfolio (e.g., GitHub, research code, or shared notebooks) is highly preferred,
  • Experience in building and evaluating machine learning models on biological data, ideally with transformer-based models (e.g., scGPT, Geneformer, ESM, ProtBERT), with a deep understanding of feature selection, model interpretability,
  • Professional experience with AI workflows, including natural language processing (NLP), retrieval-augmented generation (RAG), embeddings, vectorization of diverse data types, and working with large language models (e.g., GPT),
  • Demonstrated experience with model evaluation and experimental design in a scientific context, including setting up appropriate benchmarks and controls.

Finally, we seek candidates who embrace our values and way of working:
  • Ability to thrive in uncertainty with frequently changing priorities
  • Deep alignment with our values
  • A passion for making an impact on patients

Apply