ZipRecruiter

Log In

1

Computational Engineering Jobs in New York (NOW HIRING)

Neptune Bio

Computational Biologist

New York, NY · On-site

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 ...

Neptune Bio

Computational Biologist

New York, NY · On-site

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

Computational Plasma Physicist

Kearny, NJ

$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 ...

Thea Energy

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 ...

Oxman

Computational Designer

New York, NY · On-site

$115K - $143K/yr

EDEN is a digital design environment for the engineering and design of ecosystems , modeling the ... Role Overview OXMAN is seeking a Computational Designer to join the EDEN design team and develop ...

next page

Showing results 1-20

All JobsComputational Engineering JobsComputational Engineering Jobs in New York

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 8, 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 skills and qualifications are needed to thrive as a computational engineer?

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 does a computational engineer do?

A computational engineer develops and applies mathematical models, algorithms, and simulations to solve complex engineering problems. They often use programming languages and software tools to analyze data, optimize systems, and improve designs in fields such as aerospace, automotive, or energy. Strong skills in programming, numerical methods, and problem-solving are essential for this role.

Is computational engineering in demand?

Computational engineering is in high demand across industries such as aerospace, automotive, and energy, where advanced simulations and modeling are essential. Professionals with skills in programming, numerical methods, and software tools like MATLAB or Python are sought after for their ability to optimize designs and solve complex problems.

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 engineer?

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 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 are popular job titles related to Computational Engineering jobs in New York? For Computational Engineering jobs in New York, the most frequently searched job titles 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:
Computational Engineering jobs near you
Infographic showing various Computational Engineering job openings in New York as of August 2026, with employment types broken down into 90% Full Time, 5% Part Time, 4% Contract, and 1% Nights. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $132,942 per year, or $63.9 per hour.

Computational Biologist

Neptune Bio

New York, NY • On-site

Other

Re-posted 7 days 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.

Apply