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Generative Ai Biology Jobs (NOW HIRING)

... biology, robotics, and AI. We identify and validate new therapeutic targets and de-risk new ... Domain & Technical Growth - Remain current with the latest research trends in Generative AI ...

Domain & Technical Growth - Remain current with the latest research trends in Generative AI ... Familiarity with biological or biomedical imaging; advanced knowledge in multi-modal Phenomaps ...

Lead Generative AI Analyst

San Francisco, CA ยท On-site

$180 - $230/hr

Domain knowledge in specialized fields (e.g., Law, Gardening, Biology, US History, Academic Engineering). * 4-year accredited college degree or equivalent experience. Core Competencies Demonstrates ...

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Generative Ai Biology information

What is generative AI in biology?

Generative AI in biology refers to the use of artificial intelligence models, particularly generative models like deep learning neural networks, to create new biological data or simulate biological processes. These models can design novel proteins, predict molecular structures, and generate hypotheses for drug discovery. By leveraging large datasets and advanced algorithms, generative AI is accelerating research in genomics, synthetic biology, and personalized medicine. This technology is transforming how scientists approach complex biological problems and is rapidly becoming a vital tool in biotech and pharmaceutical industries.

How do generative AI biology specialists collaborate with interdisciplinary teams?

In Generative AI Biology, collaboration with interdisciplinary teams is crucial for success. Professionals often work closely with computational scientists, bioinformaticians, biologists, and data engineers to design experiments, validate AI-generated predictions, and interpret complex datasets. Regular meetings and collaborative platforms facilitate knowledge sharing, ensuring that AI models are both biologically relevant and technically robust. This dynamic team environment fosters innovation and enables professionals to contribute to both scientific discovery and product-driven applications.

What are the key skills and qualifications needed to thrive as a generative AI biology specialist?

To thrive as a Generative AI Biology specialist, you need a strong foundation in computational biology, machine learning, and life sciences, typically supported by an advanced degree in bioinformatics, computational biology, or a related field. Proficiency in programming languages like Python or R, experience with deep learning frameworks (such as TensorFlow or PyTorch), and familiarity with bioinformatics tools and databases are essential. Strong problem-solving abilities, interdisciplinary communication, and creativity help you bridge gaps between AI technology and biological research. These skills enable you to develop innovative models and solutions that drive advancements in biological discovery and healthcare.

What is the difference between Generative Ai Biology vs Bioinformatics Specialist?

AspectGenerative Ai BiologyBioinformatics Specialist
Required CredentialsDegree in Biology, Computer Science, or related fields; knowledge of AI and machine learningDegree in Bioinformatics, Biology, Computer Science; proficiency in data analysis and programming
Work EnvironmentResearch labs, biotech companies, AI-focused startupsResearch institutions, healthcare, biotech firms, academia
Industry UsageDeveloping AI models to generate biological data, simulate biological processesAnalyzing biological data, developing algorithms for genomics and proteomics

Generative Ai Biology focuses on creating AI models that generate or simulate biological data, combining biology and AI expertise. In contrast, Bioinformatics Specialists analyze biological data using computational tools. Both roles require strong backgrounds in biology and programming, but their core functions differ: one emphasizes AI model development, the other data analysis.

More about Generative Ai Biology jobs

What cities are hiring for Generative Ai Biology jobs?

Cities with the most Generative Ai Biology job openings:

What states have the most Generative Ai Biology jobs?

States with the most job openings for Generative Ai Biology jobs include:

Infographic showing various Generative Ai Biology job openings in the United States as of August 2026, with employment types broken down into 76% Full Time, 21% Part Time, and 3% Contract. Highlights an 64% Physical, 4% Hybrid, and 32% Remote job distribution.

Senior/Principal Machine Learning Scientist, Perturbation Biology, AI Biology & Translation (AIBT)

F. Hoffmann-La Roche AG

South San Francisco, CA โ€ข On-site

$147.80 - $320.20/hr

Other

Posted 17 days ago


Job description

Overview

A healthier future. Itโ€™s what drives us to innovate. To continuously advance science and ensure everyone has access to the healthcare they need today and for generations to come. Creating a world where we all have more time with the people we love. Thatโ€™s what makes us Roche. Advances in AI, data, and computational sciences are transforming drug discovery and development. Rocheโ€™s Research and Early Development organisations at Genentech (gRED) and Pharma (pRED) have demonstrated how these technologies accelerate R&D, leveraging data and novel computational models to drive impact. Seamless data sharing and access to models across gRED and pRED are essential to maximising these opportunities. The new Computational Sciences Center of Excellence (CoE) is a strategic, unified group whose goal is to harness this transformative power of data and Artificial Intelligence (AI) to assist our scientists in both pRED and gRED to deliver more innovative and transformative medicines for patients worldwide.

The Opportunity

We are seeking a highly motivated and collaborative Senior/Principal Machine Learning Scientist to join the Perturbation Biology group in the Department of AI for Biology & Translation (AIBT) in Genentech Research and Early Development (gRED). The successful candidate will develop the next generation of machine learning models to derive actionable insights from largeโ€‘scale highโ€‘content perturbation experiments for target and drug discovery. This role requires a deep understanding of machine learning applied to sequencingโ€‘based perturbation data, a passion for innovation and interโ€‘disciplinary research, and a commitment to improving healthcare outcomes through cuttingโ€‘edge technology. The candidate is expected to lead highโ€‘profile projects in collaboration with our therapeutic area leads, and to routinely publish work in topโ€‘tier machine learning and scientific venues.

Responsibilities
  • Design and apply predictive machine learning algorithms for labโ€‘inโ€‘theโ€‘loop perturbation screens for drug and target identification.
  • Work on and integrate a variety of different data modalities such as molecular structures, omics data, images, and text.
  • Collaborate with interdisciplinary and crossโ€‘functional teams including biologists, chemists, data scientists, and other stakeholders.
  • Build and scale machine learning techniques to massive datasets and aid in the deployment of novel machine learning algorithms.
  • Publish in topโ€‘tier machine learning venues and/or scientific journals, and present results at internal and external scientific venues, conferences, and workshops.
Qualifications
  • Educational Background: PhD degree in a quantitative field (e.g., Computer Science, Statistics, Mathematics) or in the physical or life sciences (e.g., Chemistry, Biology) with a strong quantitative focus.
  • Experience:
    • Senior ML Scientist: 0-2 years postโ€‘PhD.
    • Principal ML Scientist: 2-7 years postโ€‘PhD.
    • Proven track record of developing and applying advanced machine learning models in a research or industry setting.
    • Demonstrated interest in problems across biology and chemistry as applied to the discovery and development of treatments for disease.
  • Technical Skills: Proficiency in scientific programming in Python. Extensive experience with Machine Learning frameworks and libraries (e.g., PyTorch, JAX, Tensorflow). Strong background in statistics, probabilistic modeling, and data analysis.
  • Soft Skills: Excellent communication, collaboration, and problemโ€‘solving skills.
  • Publications: Strong publication record and experience contributing to research communities, including conferences like NeurIPS, ICML, ICLR, CVPR, ICCV, etc.
  • Preferred Practical Experience: Predictive modeling of perturbation datasets to drive experimental design; Predictive modeling and/or generative modeling on molecules and other chemistry applications; Multimodal data integration, in particular between multiple measurement modalities and/or clinical patient data.
Compensation & Benefits

Relocation benefits are NOT available for this job posting. The expected salary range for this position, based on the location of California, is $147,800 โ€“ $274,400 for the Senior ML Scientist, and $172,400 โ€“ $320,200 for the Principal ML Scientist. Actual pay will be determined based on experience, qualifications, geographic location, and other jobโ€‘related factors permitted by law. A discretionary annual bonus may be available based on individual and company performance. This position also qualifies for benefits.

Equal Opportunity & Accessibility

Genentech is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company's policy prohibits unlawful discrimination, including but not limited to discrimination on the basis of protected veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws.

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