1

Python Biology Jobs in New York (NOW HIRING)

Showing results 21-40

Python Biology information

What is a Python biologist?

A Python biologist is a professional who uses the Python programming language to analyze and interpret biological data. They often work in fields like bioinformatics, genomics, and computational biology, developing software tools to process large datasets such as DNA sequences or protein structures. Python biologists help translate complex biological problems into computational solutions, enabling researchers to gain insights that would be difficult to achieve manually.

What are the key skills and qualifications needed to thrive as a computational biologist specializing in Python?

To thrive as a Computational Biologist with a focus on Python, you need a strong background in biology, bioinformatics, and programming, typically supported by a degree in biological sciences, computer science, or a related field. Familiarity with Python libraries like Biopython, NumPy, and pandas, as well as experience with data analysis tools and version control systems such as Git, is essential. Analytical thinking, attention to detail, and effective communication are crucial soft skills for interpreting biological data and collaborating with interdisciplinary teams. These competencies enable accurate data analysis, innovative research, and effective teamwork in advancing biological discoveries.

How do Python biology professionals typically collaborate with interdisciplinary teams in research settings?

Python Biology professionals often work closely with biologists, data scientists, and software engineers to analyze complex biological data. Collaboration usually involves translating biological questions into computational tasks, developing data pipelines, and presenting findings in a way that is accessible to both technical and non-technical stakeholders. Regular meetings and code reviews are common practices, ensuring that the software developed aligns with the scientific goals of the project. This interdisciplinary approach not only enhances research outcomes but also provides valuable learning and growth opportunities for team members.

What is the difference between Python Biology vs Bioinformatics Analyst?

AspectPython BiologyBioinformatics Analyst
Required CredentialsBiology degree, Python programming skillsBiology or related degree, Python and data analysis skills
Work EnvironmentResearch labs, biotech companies, academic institutionsResearch institutions, biotech firms, healthcare organizations
Industry UsageData analysis, modeling biological systems using PythonAnalyzing biological data, developing pipelines, interpreting results

Python Biology focuses on applying Python programming to biological research, often emphasizing coding and data modeling. Bioinformatics Analysts combine biological knowledge with data analysis skills, including Python, to interpret complex biological datasets. Both roles require programming skills and work in similar environments, but Python Biology is more research and development-oriented, while Bioinformatics Analysts focus on data interpretation and analysis.

Is Python useful for biology?

Python is widely used in biology-related jobs for data analysis, modeling, and automation of research workflows. Skills in Python, along with knowledge of biological data formats and libraries like Biopython, are valuable for roles in bioinformatics, computational biology, and systems biology.

What cities in New York are hiring for Python Biology jobs?

Cities in New York with the most Python Biology job openings:

Computational Biologist, Synthetic Spatial Omics

New York, NY • On-site, Remote

Full-time

Retirement, PTO

Posted 27 days ago


Key responsibilities

  • Lead the computational analysis of multiplexed imaging, spatial omics, and other high-dimensional datasets generated from endogenous and engineered immune cells.

  • Develop novel computational and machine-learning approaches to identify interpretable biological, organizational, and regulatory principles from cellular morphology, molecular state, subcellular organization, and spatial context.

  • Work closely with experimental scientists to design studies, define controls, establish quantitative benchmarks, and iteratively improve experimental and computational workflows.


Job description

Biohub is the first large-scale initiative bringing frontier AI models, massive compute, and frontier experimental capabilities under one roof. We're building a general-purpose system to accelerate scientific discovery, integrating frontier AI models, biological foundation models, and lab capabilities, with the ultimate goal of curing disease. Our technology powers scientists around the world, translating AI capabilities into tools that accelerate research everywhere.
The Team
Our immune cell reprogramming team integrates foundational research on immunology and disease biology with AI-modeling to develop engineered cells that harness our own immune system to detect and treat early signs of age-related diseases, like cancer, Alzheimer's, and Parkinson's. These technologies will enable precise, context-dependent therapeutic responses only when and where it is needed. You can learn more about our work here.
Our work brings together three powerhouse universities - Columbia University, The Rockefeller University, and Yale University - into a single collaborative technology and discovery engine.
Our Vision
  • Pursue large scientific challenges that cannot be pursued in conventional environments
  • Enable individual investigators to pursue their riskiest and most innovative ideas
  • Facilitate research by scientists and clinicians at our home institutions and beyond

We are a team of passionate individuals powered by technology, guided by scientific research, and driven by collaboration, working toward a mission to cure or prevent all disease.
The Opportunity
The newly established Laboratory of Synthetic Spatial Omics at CZ Biohub NY (https://takeilab.org/) advances our understanding of engineered immune cell function within their native microenvironment to design better cell therapeutic approaches. Toward this goal, we develop and integrate state-of-the-art immune cell engineering, imaging-based and sequencing-based multi-omics, and machine learning/AI frameworks. We bring together scientists with diverse expertise to pursue highly interdisciplinary scientific challenges.
We are seeking a creative and highly collaborative Computational Biologist to develop and apply computational methods for imaging-based multi-omics datasets generated in the laboratory. The primary focus of this position will be to uncover interpretable relationships among molecular state, cellular morphology, subcellular organization, engineered design, and tissue context in endogenous and engineered immune cells. The successful candidate will work closely with experimental scientists to shape studies, design analytical strategies, and drive projects from experimental planning through biological interpretation and publication. This position offers the opportunity to develop novel computational frameworks at the intersection of spatial omics, synthetic biology, immunology, and machine learning.
Interested candidates should submit the following documents:
  • Cover Letter detailing research interests, motivations, and career goals.
  • Full Curriculum Vitae (CV) highlighting major achievements, including a summary of significant publications.

Please note that the target start date for this role is January 2027.
What You'll Do
  • Lead the computational analysis of multiplexed imaging, spatial omics, and other high-dimensional datasets generated from endogenous and engineered immune cells.
  • Develop novel computational and machine-learning approaches to identify interpretable biological, organizational, and regulatory principles from cellular morphology, molecular state, subcellular organization, and spatial context.
  • Build models that predict molecular states, functional outcomes, or perturbation responses from imaging and multimodal measurements.
  • Work closely with experimental scientists to design studies, define controls, establish quantitative benchmarks, and iteratively improve experimental and computational workflows.
  • Develop robust, reproducible, and scalable analysis pipelines and software.
  • Depending on expertise, contribute to the computational design or evaluation of synthetic receptors, transcription factors, protein circuits, and other programmable molecular components.
  • Contribute to preprints, publications, presentations, and open science practices.
What You'll Bring
Essential -
  • PhD in Computational Biology, Computer Science, Biomedical Engineering, or a closely related discipline.
  • Minimum 2 years of experience in developing AI/ML-based computational frameworks.
  • Strong programming skills in Python, R, or a comparable scientific computing environment.
  • Strong track record of research productivity, including publications, and close collaboration with experimental scientists.
  • Solid foundation in cell biology and genomics.
  • Ability to independently design rigorous computational frameworks, troubleshoot complex workflows, and drive projects to completion.
  • Collaborative mindset and strong scientific communication skills.

Nice to have -
  • Evidence of methodological creativity through the development of computational methods, software, or novel analytical frameworks.
  • Experience analyzing multiplexed microscopy, tissue imaging, or imaging-based spatial omics data.
  • Experience with cell segmentation, representation learning, spatial statistics, morphological profiling, or subcellular image analysis.
  • Experience analyzing single-cell, perturbation, or multimodal omics datasets.
  • Experience with computational protein design, de novo receptor design, transcriptional regulation, or synthetic protein circuits.
  • Familiarity with immunology, engineered immune cells, or synthetic biology.
Compensation
The New York City, NY base pay range for a new hire in this role is $153,000.00 - $191,000.00. New hires are typically hired into the lower portion of the range, enabling employee growth in the range over time. Actual placement in range is based on job-related skills and experience, as evaluated throughout the interview process.
This position may be eligible to participate in our discretionary annual performance bonus program. Bonus eligibility and targets are determined in accordance with our total rewards philosophy and may vary by role.
Better Together
As we grow, we're excited to strengthen in-person connections and cultivate a collaborative, team-oriented environment. This role is a hybrid position requiring you to be onsite for at least 60% of the working month, approximately 3 days a week, with specific in-office days determined by the team's manager. The exact schedule will be at the hiring manager's discretion and communicated during the interview process.
Benefits for the Whole You
We're thankful to have an incredible team behind our work. To honor their commitment, we offer a wide range of benefits to support the people who make all we do possible.
  • Provides a generous employer match on employee 401(k) contributions to support planning for the future.
  • Paid time off to volunteer at an organization of your choice.
  • Funding for select family-forming benefits.
  • Relocation support for employees who need assistance moving

If you're interested in a role but your previous experience doesn't perfectly align with each qualification in the job description, we still encourage you to apply as you may be the perfect fit for this or another role.
#LI-Hybrid