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Computational Engineering Jobs in New York (NOW HIRING)

Position Summary We are seeking a Computational Biologist who is passionate about using data-driven ... Expertise in data engineering and reproducible research tools (e.g., Docker, Nextflow, Snakemake ...

Position Summary We are seeking a Computational Biologist who is passionate about using data-driven ... Expertise in data engineering and reproducible research tools (e.g., Docker, Nextflow, Snakemake ...

Thea Energy is leveraging recent breakthroughs in stellarator physics and engineering to create a ... We are seeking highly motivated Computational Plasma Physicists to join our team, focusing on ...

Computational Plasma Physicist

Kearny, NJ · On-site

$120K - $140K/yr

Thea Energy is leveraging recent breakthroughs in stellarator physics and engineering to create a ... We are seeking highly motivated Computational Plasma Physicists to join our team, focusing on ...

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Computational Engineering information

See New York salary details

$53.1K

$132.9K

$150.4K

How much do computational engineering jobs pay per year?

As of Aug 1, 2026, the average yearly pay for computational engineering in New York is $132,942.00, according to ZipRecruiter salary data. Most workers in this role earn between $122,000.00 and $143,900.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Computational Engineering position, and why are they important?

To thrive as a Computational Engineer, a strong background in mathematics, computer science, and engineering fundamentals is essential, generally supported by a degree in computational engineering or a related field. Familiarity with programming languages like Python, MATLAB, or C++, as well as experience using simulation software and high-performance computing systems, is typically required. Analytical thinking, effective communication, and problem-solving abilities are important soft skills for collaboration and innovation. These competencies enable Computational Engineers to develop accurate models, optimize complex systems, and deliver efficient solutions in multidisciplinary environments.

What engineers make $500,000?

Senior engineers in specialized fields such as software engineering, petroleum engineering, and aerospace engineering can earn $500,000 or more annually, especially with experience, advanced skills, and leadership roles. High compensation often includes bonuses, stock options, or profit sharing, particularly in technology and energy sectors.

What can you do with a computational engineering degree?

A computational engineering degree prepares individuals for roles involving modeling, simulation, and analysis of complex systems across industries such as aerospace, automotive, energy, and manufacturing. Graduates often work as simulation engineers, data analysts, or software developers, utilizing programming languages like Python, C++, and MATLAB, and may require knowledge of high-performance computing environments. The degree provides a foundation for problem-solving in engineering design, optimization, and research projects.

Can a computer engineer make $500,000?

Computer engineering roles typically do not reach $500,000 annually, but senior positions such as principal engineers, technical directors, or those in high-paying industries like finance or tech startups can achieve this level with experience, bonuses, and stock options. Advanced skills, certifications, and leadership responsibilities often contribute to higher compensation in this field.

What are some common challenges Computational Engineers face in their work?

Computational Engineers often encounter complex, large-scale problems that require developing accurate and efficient computational models, which can be challenging due to intricacies in physical systems or computational resource limitations. Managing tight project deadlines while ensuring high-quality results and adapting to rapidly evolving technology are also common aspects of the role. Collaboration across multidisciplinary teams—often with scientists, designers, or other engineers—requires strong communication and adaptability. Embracing these challenges can help Computational Engineers expand their expertise and positively impact project outcomes.

What is a Computational Engineering job?

A Computational Engineering job involves using mathematical models, algorithms, and computer simulations to analyze and solve engineering problems. It combines principles from computer science, applied mathematics, and engineering to improve product design, optimize systems, and enhance efficiency in various industries. Professionals in this field develop software tools, conduct simulations, and utilize high-performance computing to solve complex engineering challenges in areas such as aerospace, automotive, energy, and healthcare.

What engineers make $300,000 a year?

Senior engineers in fields such as software, petroleum, aerospace, and electrical engineering can earn $300,000 or more annually, especially with extensive experience, advanced skills, and leadership roles. High compensation often involves working in specialized industries, holding managerial positions, or possessing advanced certifications and expertise in high-demand areas.
What are the most commonly searched types of Computational Engineering jobs in New York? The most popular types of Computational Engineering jobs in New York are:
What job categories do people searching Computational Engineering jobs in New York look for? The top searched job categories for Computational Engineering jobs in New York are:
Infographic showing various Computational Engineering job openings in New York as of July 2026, with employment types broken down into 58% Full Time, and 42% Contract. Highlights an 100% In-person job distribution, with an average salary of $132,942 per year, or $63.9 per hour.

Computational Biologist

Neptune Bio

New York, NY

Other

Re-posted 8 hours ago


Job description

Position Summary

We are seeking a Computational Biologist who is passionate about using data-driven, scalable methods to reveal biological insights. The ideal candidate is an independent thinker with strong computational and quantitative skills, and the ability to collaborate closely with both experimental and computational scientists. You will design, implement, and scale computational pipelines for single-cell perturbation datasets, while contributing to model development and experimental design.

This is a unique opportunity to join a dynamic, interdisciplinary environment and help shape Neptune Bio's computational strategy and infrastructure.

Key Responsibilities

  • Develop, innovate, and maintain advanced computational methods to process, analyze, and interpret large-scale single-cell genomics and perturbation datasets.
  • Collaborate with wet-lab and computational teams to integrate data from diverse experimental modalities and guide experimental design.
  • Build, optimize, and scale data analysis pipelines using modern cloud computing environments (e.g., AWS, GCP, Azure).
  • Contribute to Neptune Bio's data infrastructure, ensuring reproducibility, scalability, and efficient access to large datasets.
  • Stay current with advances in computational biology, machine learning, and scalable infrastructure, applying them to ongoing research challenges.
  • Communicate findings clearly through reports, visualizations, and presentations to multidisciplinary audiences.

Qualification and Education Requirements

You must have:

  • Ph.D. in Bioinformatics, Computational Biology, Computer Science, or a related quantitative field, OR equivalent experience (e.g., BS/MS with 3 years of relevant experience).
  • Proficiency in Python, R, and Unix/Linux environments
  • Demonstrated experience in single-cell or multi-omics data analysis.
  • Solid understanding of statistics, data modeling, and modern machine learning approaches.
  • Experience deploying and scaling computational pipelines on cloud platforms (AWS, GCP, or similar).
  • Strong communication skills and enthusiasm for working in a collaborative, fast-paced environment.

Additional preferred experience includes:

  • Background in functional genomics, CRISPR screens, or perturb-seq analysis.
  • Experience integrating multi-source data to derive novel and impactful insights.
  • Expertise in data engineering and reproducible research tools (e.g., Docker, Nextflow, Snakemake) as well as familiarity with cloud-native architectures and distributed compute.
  • Strong publication record demonstrating innovation in computational methods or biological data analysis.
  • Experience with deep learning frameworks such as PyTorch or TensorFlow.