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Remote Scientist Antibody Engineering Jobs (NOW HIRING)

Zenlaw

Data Scientist (Remote)

New York, NY · On-site +1

As a Data Scientist, you will be working with our engineering team to model complex problems and ... Due to the remote nature of this role, we are unable to provide visa sponsorship.

GD Resources LLC

Data Scientist - Remote Role

Remote Position Summary The Senior Data Scientist provides advanced analytical expertise supporting ... Perform exploratory data analysis, feature engineering, and model optimization. * Conduct large ...

Naval Sea Systems Command

ENGINEER/SCIENTIST

Dahlgren, VA · On-site +1

$143K - $197K/yr

You will ensure requisite system engineering discipline is applied across the portfolio (SEP, SETR ... remote or isolated sites. You must be able to travel on military and commercial aircraft for ...

Naval Sea Systems Command

ENGINEER/SCIENTIST

Dahlgren, VA · On-site +1

$143K - $197K/yr

You will provide technical oversight of science, engineering, and integration efforts for sensor ... remote or isolated sites. You must be able to travel on military and commercial aircraft for ...

Naval Sea Systems Command

ENGINEER/SCIENTIST

Dahlgren, VA · On-site +1

$69K - $156K/yr

You will conduct engineering analysis that results in the identification and recommendation of ... remote or isolated sites. You must be able to travel on military and commercial aircraft for ...

Naval Sea Systems Command

ENGINEER/SCIENTIST

Dahlgren, VA · On-site +1

$101K - $156K/yr

You will execute systems engineering, requirements engineering, systems engineering process ... remote or isolated sites. You must be able to travel on military and commercial aircraft for ...

Naval Sea Systems Command

ENGINEER/SCIENTIST

Dahlgren, VA · On-site +1

$46K - $158K/yr

You will support execution of system engineering best practices for requirements definition and ... remote or isolated sites. You must be able to travel on military and commercial aircraft for ...

YO AI Labs

AI Data Scientist - Remote

New York, NY · Remote

Remote Job Overview We are seeking experienced AI Data Science Domain Experts to contribute their ... Prompt Engineering * AI Output Evaluation * Quality Assurance * Technical Documentation * Technical ...

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Remote Scientist Antibody Engineering information

What are the key skills and qualifications needed to thrive as a remote scientist in antibody engineering?

To thrive as a Remote Scientist in Antibody Engineering, you need a strong background in molecular biology, protein engineering, and immunology, usually supported by a PhD or relevant research experience. Familiarity with laboratory automation software, bioinformatics tools, and antibody design platforms is essential, along with experience in data analysis systems. Excellent problem-solving skills, effective communication, and the ability to collaborate virtually are key soft skills for this remote role. These competencies ensure successful design, analysis, and optimization of antibodies, driving innovation and productivity in a distributed research environment.

What is the difference between Remote Scientist Antibody Engineering vs Remote Scientist Immunology?

AspectRemote Scientist Antibody EngineeringRemote Scientist Immunology
Required CredentialsPhD in Immunology, Biochemistry, or related field; experience in antibody design and engineeringPhD in Immunology, Microbiology, or related field; focus on immune system mechanisms
Work EnvironmentLaboratory research, computational modeling, biotech companiesLaboratory research, clinical settings, biotech and pharma industries
Employer & Industry UsageBiotech firms, pharmaceutical companies, research institutesResearch institutions, biotech, pharma, healthcare organizations

Remote Scientist Antibody Engineering focuses on designing and developing therapeutic antibodies, often involving protein engineering and molecular biology techniques. In contrast, Remote Scientist Immunology studies immune system functions and mechanisms, which may include antibody responses but also broader immune processes. Both roles require advanced degrees and are common in biotech and pharma industries, but they differ in their specific focus and daily tasks.

What does a remote scientist in antibody engineering do?

A Remote Scientist in Antibody Engineering works on the design, development, and optimization of antibodies for research, diagnostics, or therapeutic use, often from a location outside of a traditional laboratory. Their responsibilities may include analyzing data, performing computational modeling, collaborating with cross-functional teams, and using bioinformatics tools to predict antibody structures and functions. Remote scientists leverage digital communication and cloud-based platforms to collaborate effectively and contribute to scientific advancements without needing to be on-site. This role requires a strong background in molecular biology, immunology, and protein engineering, as well as proficiency with relevant software and databases.

How does a remote scientist in antibody engineering typically collaborate with cross-functional teams?

As a Remote Scientist specializing in Antibody Engineering, collaboration with cross-functional teams—such as bioinformatics, protein production, and clinical research—is essential. Communication is usually managed through virtual meetings, shared digital platforms, and collaborative documentation tools to ensure seamless progress on projects. While working remotely, you’ll often participate in data reviews, experimental design sessions, and troubleshooting discussions, making strong written and verbal communication skills crucial. Regular updates and clear reporting structures help maintain alignment and project momentum, even when team members are in different locations.
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Remote Scientist Antibody Engineering jobs near you
Infographic showing various Remote Scientist Antibody Engineering job openings in the United States as of August 2026, with employment types broken down into 91% Full Time, 4% Part Time, 4% Contract, and 1% Nights. Highlights an 86% Physical, 5% Hybrid, and 9% Remote job distribution.

Research Scientist, Applied Science

GenBio AI

Palo Alto, CA • On-site, Remote

$175K - $270K/yr

Full-time

Re-posted 23 days ago

Job description

GenBio AI develops multiscale foundation models to decode and simulate human biology. Our team is accelerating towards an ambitious future where scientists can unlock humanity's biggest challenges in drug discovery, healthcare, and fundamental research with AIDO (AI-Driven Digital Organism): a unified framework for predicting, simulating, and programming biology across all scales. The foundation of this vision begins today as we engineer the virtual cell to model and simulate the fundamental unit of life.

This vision has brought together a talent-dense group of product-minded researchers and engineers dedicated to bringing it to reality. Our team prides itself on our strong engineering culture and highly interdisciplinary and collaborative approach. We are based in Palo Alto, with satellite offices in Paris and Abu Dhabi.

This role combines research in AI for structural biology with the application of our models to real-world scientific challenges. The successful candidate will contribute to model development, lead computational discovery efforts in collaboration with external partners, and help translate research advances into impactful outcomes. Depending on business needs, time may be split between partner-facing scientific projects and internal research initiatives.

Job Requirements

  • PhD (or evidence of equivalent level of expertise) in Computer Science, Artificial Intelligence, Computational Biology,  or a related technical field.

  • Proven track record in research and innovation demonstrated through contributions in top-tier AI/ML (e.g., NeurIPS, ICML, CVPR, ECCV, ICCV, ICLR) and/or core biology (e.g., Nature, Science, or Cell) journals and conferences.

  • Experience in translating machine learning research into real-world scientific impact through collaborations with academic, biotechnology, or pharmaceutical partners.

  • Experience designing, executing, or supporting computational discovery campaigns in protein engineering, antibody discovery, binder design, or related therapeutic discovery efforts.

  • Experience working closely with experimental scientists and using experimental results to guide decisions.

  • Prior experience working on AI for structural biology or drug discovery in either an academic or industry setting.

  • Motivated and self-driven with the ability to operate with partial and incomplete descriptions of high-level objectives (as is typical in a start-up environment).

  • Evidence of familiarity and utilization of software engineering best practices (version controlling, documentation, etc), and open-source contributions, especially if used by others.

Preferred Qualifications

  • 3+ years of post-PhD experience in an industry or postdoc role

  • Prior experience working at either a start-up or top research industry labs (e.g., OpenAI, FAIR, Deepmind, Google Research).

  • Experience in biological structure prediction algorithms such as Alphafold2 & 3, RosettaFold. 

  • Experience in generative modeling for biological structures and sequences

  • Experience leading scientific collaborations or serving as a technical point of contact for external research partners.

  • Deep knowledge of diffusion models, flow matching, and protein sequence models

Join us as we embark on this journey to redefine the future of biology and medicine.
We are an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. GenBio AI participates in the U.S. Department of Homeland Security’s E-Verify program to confirm the employment eligibility of all newly hired employees. For more information on E-Verify, please visit www.e-verify.gov.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.