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Living In Computational Geometry Developer Jobs in New York

Neptune Bio

Computational Biologist

New York, NY

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 ...

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 ... Proficiency in Houdini for computational geometry and procedural modeling is mandatory. Experience ...

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 ...

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 ...

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All JobsLiving In Computational Geometry Developer JobsLiving In Computational Geometry Developer Jobs in New York

Living In Computational Geometry Developer information

What are the key skills and qualifications needed to thrive as a Computational Geometry Developer, and why are they important?

To thrive as a Computational Geometry Developer, you need strong mathematical proficiency, particularly in geometry and algorithms, along with a background in computer science or a related field. Familiarity with programming languages such as C++, Python, or Java, and experience using libraries like CGAL or Qhull, are typically required. Analytical thinking, problem-solving skills, and effective teamwork are crucial soft skills in this role. These competencies ensure the accurate development of geometric algorithms and the ability to collaborate on complex technical projects.

What does a Living In Computational Geometry Developer do?

A Living In Computational Geometry Developer specializes in designing, analyzing, and implementing algorithms and software that solve complex geometric problems, often in fields such as computer graphics, robotics, CAD, and geographic information systems. Their work involves working with data structures for points, lines, polygons, and other shapes, as well as optimizing computational efficiency for geometric queries and operations. They may also contribute to research, develop visualization tools, and collaborate with engineers and scientists to integrate geometric solutions into real-world applications.

What is the difference between Living In Computational Geometry Developer vs Living In Software Engineer?

AspectLiving In Computational Geometry DeveloperLiving In Software Engineer
Required CredentialsBachelor's or higher in Computer Science, Mathematics, or related field; knowledge of algorithms and geometryBachelor's or higher in Computer Science or related field; programming skills in various languages
Work EnvironmentSpecialized roles in tech, gaming, CAD, or GIS companiesBroad industry roles across tech, finance, healthcare, and more
Employer & Industry UsageUsed in industries requiring geometric computations and spatial dataWidely used across multiple industries for software development
Search & Comparison IntentPeople interested in geometric algorithms and spatial dataPeople exploring general software development careers

Living In Computational Geometry Developer focuses on geometric algorithms and spatial data, often in specialized industries, while Living In Software Engineer has a broader scope across various sectors. Both roles require programming skills and a computer science background, but their applications and industry focus differ.

What kinds of projects do Living In Computational Geometry Developers typically work on, and how do these projects impact collaboration with other teams?

Living In Computational Geometry Developers often work on projects involving the development of algorithms and software for modeling, analyzing, and visualizing geometric data. This role requires frequent collaboration with teams such as CAD engineers, simulation experts, and UI/UX designers to ensure that the computational geometry solutions integrate seamlessly with broader product requirements. Developers might also contribute to research initiatives, prototype new features, and optimize existing geometric processing pipelines. Effective communication and teamwork are key, as project success often depends on integrating complex geometry algorithms into multi-disciplinary applications.
What are popular job titles related to Living In Computational Geometry Developer jobs in New York? For Living In Computational Geometry Developer jobs in New York, the most frequently searched job titles are:
What job categories do people searching Living In Computational Geometry Developer jobs in New York look for? The top searched job categories for Living In Computational Geometry Developer jobs in New York are:
What cities in New York are hiring for Living In Computational Geometry Developer jobs? Cities in New York with the most Living In Computational Geometry Developer job openings:
Living In Computational Geometry Developer jobs near you
Infographic showing various Living In Computational Geometry Developer job openings in New York as of July 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.

Computational Biologist

Neptune Bio

New York, NY

Other

Posted 14 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.

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