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Ai Cancer Research Jobs (NOW HIRING)

Ai2

Research Engineer, Asta

Seattle, WA · On-site

... AI tools to facilitate scientific discovery in domains such as biology, cancer research, neuroscience, social science, etc. • Designing, building, and training machine learning or language models ...

The University of Chicago

Research Specialist 1

Chicago, IL · On-site

$19.23 - $26.44/hr

The lab has expertise in cancer immunology, chemical biology, and drug delivery to carry out our ... Resume (required) The University of Chicago uses AI-assisted tools to streamline and augment some ...

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$111.5K

$206K

How much do ai cancer research jobs pay per year?

As of Sep 5, 2026, the average yearly pay for ai cancer research in the United States is $200,510.00, according to ZipRecruiter salary data. Most workers in this role earn between $205,000.00 and $205,000.00 per year, depending on experience, location, and employer.

What is AI cancer research?

AI cancer research refers to the use of artificial intelligence technologies, such as machine learning and deep learning algorithms, to improve the detection, diagnosis, treatment, and understanding of cancer. Researchers use AI to analyze large datasets, including medical images and genetic information, to identify patterns and make predictions that can assist doctors and scientists. AI can help in discovering new cancer therapies, personalizing treatment plans, and enhancing early detection, ultimately aiming to improve patient outcomes and advance cancer care.

What are the key skills and qualifications needed to thrive as an AI cancer researcher?

To thrive as an AI Cancer Researcher, you need a strong background in computational biology, machine learning, and oncology, typically supported by an advanced degree in computer science, bioinformatics, or a related field. Proficiency with programming languages (such as Python or R), machine learning frameworks (like TensorFlow or PyTorch), and experience with large-scale biomedical datasets is essential. Critical thinking, problem-solving, and interdisciplinary collaboration are crucial soft skills for driving innovative research and translating findings into clinical impact. These skills and qualifications enable researchers to develop effective AI models that advance cancer diagnosis, treatment, and patient outcomes.

What are the typical challenges faced when integrating AI models into cancer research teams?

Integrating AI models into cancer research often involves navigating challenges such as ensuring high-quality, well-annotated data and fostering effective collaboration between data scientists and clinical researchers. Teams must address the complexity of medical data, maintain patient privacy, and validate AI findings with rigorous scientific standards. Open communication between AI specialists and oncology experts is crucial to develop models that are both accurate and clinically relevant, making interdisciplinary teamwork an essential part of daily responsibilities.

What is the difference between Ai Cancer Research vs Data Scientist in Healthcare?

AspectAi Cancer ResearchData Scientist in Healthcare
Required CredentialsMaster's or PhD in Oncology, Bioinformatics, or related fields; experience with AI and machine learningBachelor's or Master's in Data Science, Computer Science, or related; knowledge of healthcare data
Work EnvironmentResearch labs, hospitals, biotech companiesHospitals, healthcare tech firms, research institutions
Industry UsageFocused on applying AI to cancer diagnosis, treatment, and researchAnalyzing healthcare data for insights, predictive modeling, and decision support

Ai Cancer Research and Data Scientist in Healthcare share skills in data analysis and AI, but Ai Cancer Research specializes in oncology applications, while Data Scientists in Healthcare work across broader medical data domains.

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Ai Cancer Research jobs near you
Infographic showing various Ai Cancer Research job openings in the United States as of August 2026, with employment types broken down into 100% Full Time. Highlights an 83% In-person, and 17% Remote job distribution, with an average salary of $200,510 per year, or $96.4 per hour.

Research Engineer, Asta

Ai2

Seattle, WA • On-site

Full-time

Re-posted 24 days ago

Job description

Job Summary:
Ai2 is a non-profit AI research institute based in Seattle, focused on building breakthrough AI to solve significant global challenges. They are seeking a Research Engineer for the Asta Project, which aims to advance scientific discovery through AI tools and infrastructure, requiring expertise in machine learning and collaborative research.
Responsibilities:
• Building infrastructure to facilitate the next generation of LLM and agentic research.
• Creating AI tools to facilitate scientific discovery in domains such as biology, cancer research, neuroscience, social science, etc.
• Designing, building, and training machine learning or language models for agentic workflows.
• Bridging the gap between cutting-edge research and a widely adopted product.
• Bringing software engineering best practices to a research environment.
• Supporting and collaborating with an open-source community.
• Releasing your contributions back to the broader community in the form of open source software, model releases, and additions to Ai2’s public API and open research datasets, as well as technical reports.
Qualifications:
Required:
• A bachelor’s degree in CS/EE/Data Science/Applied Mathematics/Statistics/ML/NLP, or a related field, or equivalent relevant experience, and expertise in building ML infrastructure.
• 2+ years of experience building agentic infrastructure that handles tools, skills, and other artifacts.
• 2+ years of experience building infrastructure that handles data preprocessing/transformation and machine learning model training, evaluation, inference, and deployment.
• Knowledge of modern deep learning, natural language processing, and reinforcement learning techniques.
• Strong software engineering skills, particularly around building performant systems and debugging.
• Must have experience with Python and PyTorch/Jax/Tensorflow, agentic frameworks (e.g., MCP), as well as feel at ease in picking up new programming languages, libraries, or APIs as tools as project needs evolve.
• Familiarity with cloud compute resources (e.g., GCP, AWS, Modal) and containerization (e.g., Docker).
• Strong collaboration and communication skills - our environment is small and collaborative, and we'd like you to thrive while working closely with others, sometimes with complementary skills/perspectives.
Preferred:
• Advanced degree in CS/EE/Data Science/Applied Mathematics/Statistics/ML/NLP or related fields and/or relevant and equivalent engineering experience.
• Contributions to open-source ML or research libraries (e.g., spaCy, AllenNLP, transformers, langchain).
• Experience successfully operating at scale in a production setting.
• Experience in HPC settings.
• Curiosity about AI research.
Company:
We are a Seattle-based non-profit AI research institute founded in 2014 by the late Paul Allen. Founded in 2014, the company is headquartered in Seattle, USA, with a team of 201-500 employees. The company is currently Growth Stage.

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