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Science & Research · Updated Aug 2026

Bioinformatics Scientists

Conduct research using bioinformatics theory and methods in areas such as pharmaceuticals, medical technology, biotechnology, computational biology, proteomics, computer information science, biology and medical informatics. May design databases and develop algorithms for processing and analyzing genomic information, or other biological information.

JVS 2.0.0-phase4b
AI Exposure
79/100
Very high

How much of this occupation’s work can be materially affected by current AI systems.

Replacement Risk
70/100
High

How likely exposure is to translate into reduced human demand.

Includes provisional estimates for AI adoption pressure and labour-market resilience. How this is measured

Evidence quality
Confidence83/100
Task coverage86%

Confidence reflects task coverage, mapping and capability-evidence quality, and how much of the score rests on provisional inputs.

Task-level evidence

What is driving the score?

Occupation scores are built from the task mix—not a single prediction about a job title.

JVS 2.0.0-phase4b
TaskImportanceAI impactExposure
Consult with researchers to analyze problems, recommend technology-based solutions, or determine computational strategies.High
78
Develop new software applications or customize existing applications to meet specific scientific project needs.High
80
Create novel computational approaches and analytical tools as required by research goals.High
79
Analyze large molecular datasets, such as raw microarray data, genomic sequence data, or proteomics data, for clinical or basic research purposes.Medium
80
Keep abreast of new biochemistries, instrumentation, or software by reading scientific literature and attending professional conferences.Medium
80
Manipulate publicly accessible, commercial, or proprietary genomic, proteomic, or post-genomic databases.Medium
80
Direct the work of technicians and information technology staff applying bioinformatics tools or applications in areas such as proteomics, transcriptomics, metabolomics, or clinical bioinformatics.Medium
73
Compile data for use in activities, such as gene expression profiling, genome annotation, or structural bioinformatics.Medium
81
Communicate research results through conference presentations, scientific publications, or project reports.High
78
Design and apply bioinformatics algorithms including unsupervised and supervised machine learning, dynamic programming, or graphic algorithms.Medium
79
Provide statistical and computational tools for biologically based activities, such as genetic analysis, measurement of gene expression, or gene function determination.Medium
78
Improve user interfaces to bioinformatics software and databases.Medium
78
Confer with departments, such as marketing, business development, or operations, to coordinate product development or improvement.Medium
79
Instruct others in the selection and use of bioinformatics tools.Medium
79
Collaborate with software developers in the development and modification of commercial bioinformatics software.Medium
80
Prepare summary statistics of information regarding human genomes.Low
81
Most exposed

Where AI can do more

Routine, digitized, and highly repeatable tasks face the greatest pressure.

  1. Compile data for use in activities, such as gene expression profiling, genome annotation, or structural bioinformatics.81
  2. Prepare summary statistics of information regarding human genomes.81
  3. Develop new software applications or customize existing applications to meet specific scientific project needs.80
  4. Analyze large molecular datasets, such as raw microarray data, genomic sequence data, or proteomics data, for clinical or basic research purposes.80
Hardest to automate

Where people still matter

These tasks score lowest on automation feasibility—physical presence, judgement, accountability and real-world variability all resist end-to-end automation.

  1. Direct the work of technicians and information technology staff applying bioinformatics tools or applications in areas such as proteomics, transcriptomics, metabolomics, or clinical bioinformatics.01
  2. Consult with researchers to analyze problems, recommend technology-based solutions, or determine computational strategies.02
  3. Improve user interfaces to bioinformatics software and databases.03
  4. Communicate research results through conference presentations, scientific publications, or project reports.04
  5. Design and apply bioinformatics algorithms including unsupervised and supervised machine learning, dynamic programming, or graphic algorithms.05
Where else this work leads

Related occupations

Occupations O*NET links to this one. Relatedness reflects shared work, not a claim that these roles are safer.

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Beyond AI capability

Adoption and labour-market outlook

Structural factors are kept separate from raw capability so you can see what actually resists automation. Adoption pressure and labour-market resilience are still provisional models—25% of this occupation’s replacement-risk weight rests on them.

Human dependency62
Physical dependency20
Adoption pressure60
Labour-market resilience53
Methodology & sources

O*NET 30.3 occupational data interpreted through the JobsVsAI capability, automation and structural-constraint models.

Confidence83/100
CalculatedAug 21, 2026
Read methodology →