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Virtual Biology Jobs (NOW HIRING)

Adapts instruction using visual diagrams, virtual lab simulations, and MCAT-aligned practice to support pre-medical, biology major, and general education students at the college level. * Effective ...

Adapts instruction using visual diagrams, virtual lab simulations, and MCAT-aligned practice to support pre-medical, biology major, and general education students at the college level. * Effective ...

Adapts instruction using visual diagrams, virtual lab simulations, and MCAT-aligned practice to support pre-medical, biology major, and general education students at the college level. * Effective ...

Adapts instruction using visual diagrams, virtual lab simulations, and MCAT-aligned practice to support pre-medical, biology major, and general education students at the college level. * Effective ...

Adapts instruction using visual diagrams, virtual lab simulations, and MCAT-aligned practice to support pre-medical, biology major, and general education students at the college level. * Effective ...

Adapts instruction using visual diagrams, virtual lab simulations, and MCAT-aligned practice to support pre-medical, biology major, and general education students at the college level. * Effective ...

Adapts instruction using visual diagrams, virtual lab simulations, and MCAT-aligned practice to support pre-medical, biology major, and general education students at the college level. * Effective ...

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Virtual Biology information

What are the key skills and qualifications needed to thrive as a Virtual Biology Instructor, and why are they important?

To excel as a Virtual Biology Instructor, you need a solid background in biological sciences, often supported by a relevant degree and teaching certification. Familiarity with online learning platforms, digital laboratory simulations, and virtual classroom tools is essential. Strong communication, adaptability, and digital engagement skills help create an interactive and supportive learning environment. These competencies ensure effective delivery of complex biological concepts and foster student success in remote education settings.

How do Virtual Biology professionals typically collaborate with educators and students in an online learning environment?

Virtual Biology professionals often work closely with educators to design and deliver engaging, interactive science content tailored for remote learners. They may use digital labs, simulations, and virtual classrooms to facilitate hands-on experiences and support student understanding. Regular communication with teachers and learners is key, as is adapting content based on feedback and learning outcomes. Collaboration tools and scheduled meetings are commonly used to ensure smooth coordination and continuous improvement of the curriculum.

What is a Virtual Biologist?

A Virtual Biologist is a professional who conducts biological research, analysis, or education remotely using digital tools and technology. They may work in various fields such as genetics, ecology, or molecular biology, leveraging software for simulations, data analysis, and virtual collaboration. Virtual Biologists often participate in online teaching, remote research projects, and virtual labs, making biological sciences accessible from anywhere. This role is increasingly important as more scientific work shifts to digital and remote environments.

What is the difference between Virtual Biology vs Virtual Chemistry?

AspectVirtual BiologyVirtual Chemistry
Required CredentialsBachelor's degree in Biology or related field; teaching certification often preferredBachelor's degree in Chemistry or related field; teaching certification often preferred
Work EnvironmentOnline platforms, virtual classrooms, remote teachingOnline labs, virtual classrooms, remote instruction
Industry UsageEducational institutions, online tutoring companiesEducational institutions, online tutoring companies
Common Search IntentCompare virtual biology teaching roles, online biology tutoringCompare virtual chemistry teaching roles, online chemistry tutoring

Virtual Biology and Virtual Chemistry both involve online teaching and tutoring roles within educational settings. While they share similar credentials and work environments, Virtual Biology focuses on biological sciences, whereas Virtual Chemistry centers on chemical sciences. Understanding these differences helps job seekers find roles aligned with their expertise and interests in the virtual education industry.

More about Virtual Biology jobs
What cities are hiring for Virtual Biology jobs? Cities with the most Virtual Biology job openings:
What are the most commonly searched types of Biology jobs? The most popular types of Biology jobs are:
What states have the most Virtual Biology jobs? States with the most job openings for Virtual Biology jobs include:
What job categories do people searching Virtual Biology jobs look for? The top searched job categories for Virtual Biology jobs are:
Infographic showing various Virtual Biology job openings in the United States as of May 2026, with employment types broken down into 4% As Needed, 33% Full Time, 50% Part Time, and 13% Contract. Highlights an 51% Physical, 3% Hybrid, and 46% Remote job distribution.

Sr Staff Data Scientist, Virtual Biology Initiative

Biohub

Redwood City, CA • On-site, Remote

Other

Retirement, PTO

This job post has expired today. Applications are no longer accepted.


Job description

Sr Staff Data Scientist, Virtual Biology Initiative, AI Research

New York, NY (Hybrid); Redwood City, CA (Hybrid)

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 Opportunity

In April 2026, Biohub launched the Virtual Biology Initiative—a $500 million, five-year commitment to galvanize a global effort to build predictive models of the human cell. This initiative will bring together leading institutions to generate the multi-modal biological data, at unprecedented scale, that will power the next generation of AI models for biology while producing datasets of unprecedented size.

Our data science team defines the algorithms and processing approaches that turn raw biological measurements into rich representations models can actually learn from. That includes designing data formats and representations optimized for AI use cases, building cost-aware processing pipelines that balance expressiveness with efficiency, developing scalable QC and validation frameworks across modalities, creating agent-augmented curation tools for metadata extraction and ontology mapping, and building the cross-modal entity resolution and semantic infrastructure that ties it all together.

Both the scale and domain are active research areas. How do you tokenize a cell image? How do you represent a perturbation experiment? How do you combine transcriptomics with imaging in a way that preserves biological meaning? These questions don't have established answers. We need scientific leaders who can work at this frontier: people who understand biological measurement deeply, think creatively about data representations, sampling, and tokenization strategies, and can translate that thinking into data representations that enable novel training architectures.

You'll work directly with scientists, computational biologists, data engineers, and AI researchers to define model input and biological evaluations. You will operate with broad scope and high autonomy, influencing roadmap decisions across teams while mentoring senior individual contributors. Success in this role means creating and implementing data systems that are not only large, but adaptive, interpretable, and scientifically grounded—accelerating progress toward robust biological frontier models and ultimately advancing human health.

What You'll Do
  • Set technical vision and strategy for the design of data representations and tokenization strategies across biological data types—including imaging, sequencing, and multimodal data—that enable novel model architectures
  • Develop, deploy and validate approaches for combining heterogeneous data modalities into unified training frameworks, designing for robustness to noise, bias, and batch effects
  • Evaluate model performance, identifying which biological signals are captured or lost and iterating to improve
  • Partner deeply with ML engineers and AI researchers to co-design datasets and optimize model training, evaluation, and generalization
  • Lead cross-functional initiatives spanning data engineering, infrastructure, science, and product, aligning technical execution with long-term scientific goals
  • Identify and drive new data acquisition and generation opportunities, from consortium partnerships to internal experimental pipelines
  • Serve as a technical mentor and leader, raising the bar for data science and ML rigor across the organization
What You'll Bring
  • 12+ years of experience (or PhD + 7 years) working with large-scale biological datasets, including ownership of end-to-end data products
  • Deep expertise in at least one of: (a) imaging data—microscopy, cell phenotyping, spatial biology, and the data characteristics of image-based biological measurement; or (b) genomics data—bulk and single-cell sequencing, functional genomics, epigenomics, transcriptomics, spatial biology, and/or multi-omics
  • Understanding of how to transform raw biological data into AI-ready datasets, including familiarity with scientific best practices, noise characteristics, batch effects, and quality assessment specific to your domain
  • Experience with tokenization strategies for non-text data (images, sequences, graphs, time series) or with creating data representations and feature engineering for machine learning in scientific or biological contexts
  • Strong expertise in data science and statistical modeling; familiarity with modern ML architectures (transformers, diffusion models, or similar) and how data representation choices affect learning
  • Strong computational skills; demonstrated ability to design robust, extensible data architectures
  • Excellent communication and leadership skills, with the ability to translate between biology, ML, and engineering audiences and align teams to deliver complex projects
  • Creative, first-principles thinking about how to structure data for learning
Compensation

The Redwood City, CA & New York City, NY base pay range for a new hire in this role is $241,000.00 - $331,100.00. 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.

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.