1

Scientific Computing Internship Jobs in New York

Lead Machine Learning Engineer

New York, NY ยท On-site +1

$112K - $147K/yr

... Data Science teams * Inform your ML infrastructure decisions using your understanding of ML ... distributed computing (Internship experience does not apply) * At least 4 years of experience ...

Lead Machine Learning Engineer (IC)

New York, NY ยท On-site

$112K - $147K/yr

... Data Science teams * Inform your ML infrastructure decisions using your understanding of ML ... distributed computing (Internship experience does not apply) * At least 4 years of experience ...

Lead Machine Learning Engineer (IC)

New York, NY ยท On-site +1

$112K - $147K/yr

... Data Science teams * Inform your ML infrastructure decisions using your understanding of ML ... distributed computing (Internship experience does not apply) * At least 4 years of experience ...

next page

Showing results 1-20

Scientific Computing Internship information

What is a scientific computing internship?

A Scientific Computing Internship is a temporary position where students or recent graduates work on projects involving computational methods to solve scientific problems. Interns typically assist with programming, data analysis, mathematical modeling, and using specialized software to support research in fields like physics, biology, or engineering. The internship provides hands-on experience with real-world scientific challenges, often in academic, government, or industry research settings. These opportunities help interns develop technical skills, gain exposure to the research process, and build professional networks in the scientific computing field.

What types of projects might I work on during a scientific computing internship?

As a Scientific Computing Intern, you may be involved in projects such as developing simulation models, optimizing computational algorithms, or analyzing large datasets for scientific research. Interns often collaborate closely with researchers and software engineers, contributing to code development, data processing, or scientific visualization tasks. These projects provide hands-on experience with programming languages like Python, MATLAB, or C++, and exposure to high-performance computing environments. The collaborative and interdisciplinary nature of the work allows you to build both technical and teamwork skills which are valuable for future roles in academia or industry.

What are the key skills and qualifications needed to thrive as a scientific computing intern, and why are they important?

To thrive as a Scientific Computing Intern, you generally need a solid background in mathematics, programming (often Python, C++, or MATLAB), and data analysis, typically supported by coursework in computer science or a related STEM field. Familiarity with scientific computing tools and libraries such as NumPy, SciPy, and version control systems like Git is common, and experience with high-performance computing environments is a plus. Strong problem-solving abilities, attention to detail, and effective communication skills help interns collaborate with research teams and present complex findings clearly. These qualifications are crucial for efficiently supporting research projects and contributing to innovative scientific solutions.

What is the difference between Scientific Computing Internship vs Data Analyst Internship?

AspectScientific Computing InternshipData Analyst Internship
Required CredentialsTypically requires a background in computer science, mathematics, or engineering; familiarity with programming languages like Python, C++, or MATLABUsually requires a degree in statistics, mathematics, or related fields; skills in SQL, Excel, and data visualization tools
Work EnvironmentResearch labs, academic institutions, or R&D departments within tech or engineering firmsBusiness settings, finance, marketing, or healthcare organizations
Employer & Industry UsageUsed in scientific research, simulations, and modeling projectsApplied in business analytics, reporting, and data-driven decision making

While both internships involve working with data and computational tools, Scientific Computing Internships focus on scientific research, simulations, and technical problem-solving, whereas Data Analyst Internships emphasize analyzing business data to inform decisions. The choice depends on your career interests in research versus business analytics.

What are the most commonly searched types of Scientific Computing jobs in New York?

The most popular types of Scientific Computing jobs in New York are:

What cities in New York are hiring for Scientific Computing Internship jobs?

Cities in New York with the most Scientific Computing Internship job openings:

Flatiron Research Fellow, Developmental Dynamics, Center for Computational Biology

Flatiron Institute

NY โ€ข On-site

Full-time

Re-posted 9 days ago


Job description

Description
The Center for Computational Biology (CCB) of the Simons Foundation's Flatiron Institute is actively seeking enthusiastic, full-time post-doctoral Flatiron Research Fellows to join its Developmental Dynamics group.
The goal at CCB is to advance the understanding of fundamental and historically challenging biological processes by developing theory, innovative modeling tools for large-scale biophysical simulations, and computational frameworks for analyzing increasingly large and complex experimental datasets. Living systems are built hierarchically; as such, CCB's research activities span several scales of biological organization, bridging the gap between microscopic detail and large-scale behaviors, and providing natural continuity between our groups' efforts. CCB currently comprises more than 45 research and data scientists at career stages from recent Ph.D. graduates through senior scientists, as well as visiting scientists, guest researchers, graduate students, interns, and administrative support staff. For a full description of CCB research areas and scientific staff, please see our website.
The Developmental Dynamics group combines experiments, theory and computing to elucidate the contributions of encoded genomic instructions and self-organizing physical mechanisms to embryonic development. Its theoretical and computational work is designed to integrate and abstract rapidly accumulating heterogeneous datasets, to propose critical tests of multiscale regulatory mechanisms, and to guide our own genetic and imaging experiments. The group's research is organized around three main themes: the mechanistic modeling of pattern formation and morphogenesis; the synthesis and decomposition of developmental trajectories; and the modeling of human developmental defects.
We are looking for candidates interested in data-driven modeling of biological systems, especially in the context of behavioral changes during postembryonic development. We have devised a throughput approach for recording such changes in Drosophila and are evaluating a range of data analysis and modeling for data mining.
POSITION DESCRIPTION
Flatiron Research Fellows in CCB are individuals at the postdoctoral level with backgrounds in one or more of the following areas: computational biology, computer science, applied mathematics, computational biology, biophysics, computer science, engineering, mathematical physics, or related disciplines.
Reporting to Research Scientists, Data Scientists or the Center Director, as appropriate, Fellows are expected to carry out an active research program that can be independently directed and/or involve substantial collaboration with other members of CCB or the Flatiron Institute. In addition to their research, Fellows help build the rich scientific community at CCB and the Flatiron Institute by participating in seminars, colloquia, and group meetings; developing their software, mathematical and computational expertise through internal education opportunities; and sharing their knowledge through scientific publications, presentations, and/or software releases, with the financial support of the Institute. Fellows have access to the Flatiron Institute's powerful scientific computing resources.
Responsibilities include but are not limited to:
  • Performing theoretical and computational research
  • Developing, implementing and maintaining scientific software
  • Participating in the organization of CCB and Flatiron-wide collaborative activities including seminars, workshops and meetings
  • Participating in the preparation of manuscripts for publication and of presentations at scientific conferences
  • Assisting in student mentorship
  • Sharing expertise and providing training and guidance to CCB staff and visitors as needed.

FRF positions are generally two-year appointments that can be renewed for a third year, contingent on performance. Fellows will be based, and have a principal office or workspace, at the Simons Foundation's offices in New York City. Fellows may also be eligible for subsidized housing within walking distance of the Flatiron Institute.
For more information about careers at the Flatiron Institute, please click here.
Qualifications
Education
  • Ph.D. in a relevant field (applied mathematics, statistics, computational biology, biophysics, computer science, engineering, mathematical physics, or related disciplines)

Related Skills & Other Requirements
  • Demonstrated abilities in mathematical modeling, analysis and/or scientific computation, scientific software and algorithm development, data analysis and inference, and image analysis
  • Ability to do original and outstanding research in computational biology, and expertise in computational methods, data analysis, software and algorithm development, modeling machine learning, and scientific simulation
  • Ability to work well in an interdisciplinary environment, and to collaborate with experimentalists
  • Strong oral and written communication, data documentation, and presentation skills

Compensation and Benefits
  • The full-time annual compensation for this position is $91,000.
  • In addition to competitive salaries, the Simons Foundation provides employees with an outstanding benefits package.

Application Instructions
To apply, please submit the following via the application portal:
  • Cover Letter, which should include a summary of applicants' most significant contributions in graduate school
  • Curriculum Vitae with publications list and, if relevant, links to software
  • Research Statement of no more than three (3) pages describing the applicant's past important results, current and future research interests which may include both scientific topics and algorithm and software development, and potential synergies with activities at CCB
  • Letters of Recommendation, at least two (2).

Applications for available positions that begin in 2026 will generally be reviewed beginning November 2025, and will be considered on a rolling basis until the positions are filled.
SELECTION CRITERIA
Applications will be evaluated based on:
  • Past research accomplishments
  • The proposed research program
  • The synergy of applicant's expertise and research proposal topic with existing CCBA staff and research programs, and potential to cross boundaries between CCB groups and/or the Flatiron Institute's other research centers.

Any queries about the application process or about CCB should be directed to ccbjobs@flatironinstitute.org. Queries about CCB may also be directed to scientific staff at CCB.