Medical scientists (except epidemiologists) Medical Scientists, Except Epidemiologists
職業コード: 19-1042（SOC） 技能移住対象職業 総合 6.8/10
Medical scientists study mechanisms of human disease and ways to improve health, involving clinical research, drug development, etc., typically requiring a PhD.
評価 · 総合 6.8/10i
In the AI era: what happens to Medical scientists (except epidemiologists)
AI's impact on medical scientists (except epidemiologists) is mixed: routine data analysis and literature review tasks will be automated, but experimental design, clinical translation, and complex reasoning are enhanced by AI. Overall career outlook is stable but requires proactive adaptation.
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Partially replaces experimental and computational work of medical scientists in protein structure resolution and drug target identification, accelerating new drug development and disease mechanism research.
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Partially replaces medical scientists in literature review, data mining, and hypothesis generation, improving efficiency in extracting insights from scientific literature.
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Partially replaces medical scientists in compound testing during early drug screening, significantly reducing time and cost, improving candidate drug discovery efficiency.
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Partially replaces medical scientists in disease mechanism analysis and drug repositioning by integrating multi-source data through AI to generate new hypotheses.
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Partially replaces medical scientists' work in molecular design and optimization; AI automatically generates and evaluates candidate drug molecules, reducing manual iteration.
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Partially replaces medical scientists in cell experiment data analysis and phenotype screening, with AI processing large amounts of image data and discovering drug-disease associations.
- Routine data analysis and statistical tests (e.g., running SPSS/SAS scripts)
- Initial screening for systematic reviews and meta-analyses
- Standardized in vitro experimental operations (e.g., ELISA, PCR batch processing)
- Clinical data management and electronic case extraction
- Repetitive calculation tasks in drug screening
- Use AI to accelerate virtual screening and molecular docking of candidate drugs
- Discovering new biomarkers from multi-omics data through machine learning
- AI assists in writing research papers, generating charts and summaries.
- Use natural language processing to quickly track the latest literature trends
- AI-based clinical trial design optimization and toxicity prediction
- Cross-disciplinary hypothesis generation and innovative experiment design
- Research ethics judgment and subject safety oversight
- Deep collaboration with clinicians and translational medical decisions
- Handle unpredictable experimental anomalies and result interpretation
- Human trust and responsibility attribution in academic/regulatory exchanges
- Python/R/Bioinformatics programming
- Machine learning and deep learning fundamentals (TensorFlow/PyTorch)
- AI-assisted drug discovery tools (e.g., AlphaFold, molecular dynamics)
- clinical trial design and regulations (FDA/ICH guidelines)
- Data ethics and AI explainability
- Cross-team communication and project management
Entry-level positions (e.g., research assistants, technicians) are decreasing due to AI automation of some lab work, but interdisciplinary requirements (bioinformatics, computational modeling) are increasing, effectively raising entry barriers and intensifying competition for junior roles.
Over the next 5 years, medical scientists should deeply integrate AI tools into research workflows: from data generation to hypothesis testing, actively learn bioinformatics and computational modeling, and shift toward translational research or precision medicine. Maintain cutting-edge clinical knowledge and become an AI coordinator connecting lab and clinic, rather than being replaced as 'data laborers.'
給与
| 経験 | 年収 (USD) | |
|---|---|---|
| 初級（0～3年） | $60,000 ~ $90,000 | Postdoctoral or junior researcher |
| 中級（3-7年） | $90,000 ~ $130,000 | Researcher or assistant professor |
| Senior (7+ years) | $130,000 ~ $200,000 | Senior researcher or professor |
教育パス
| 段階 | 期間 | 費用 (USD) |
|---|---|---|
| Bachelor's degree | 4年 | $40,000~$180,000 |
| Doctorate (Ph.D.) | 5-6 years. | $0~$50,000 |
| Medical degree (M.D.) optional | 4年 | $200,000~$400,000 |
資格
| 資格 | 発行機関 | |
|---|---|---|
| Doctoral degree (PhD) | University | 必須 |
| Postdoctoral research experience | Research institutions | 任意 |
移住
Occupation classification code: 19-1042（SOC）
| ビザ | 詳細 |
|---|---|
| H-1B H-1B Specialty Occupation | For researchers with a bachelor's degree or higher, requires employer sponsorship with limited annual quota. |
| EB-2 Employment-Based Second Preference | Applicable to researchers with advanced degrees or exceptional skills, who may apply for green card via PERM. |
| O-1 O-1 Extraordinary Ability | Applicable to researchers with outstanding achievements in science, no quota limit. |
向いている人
- People with a strong interest in biomedical research willing to commit to long-term study
- Possess critical thinking and experimental design skills, able to withstand research pressure.
- Researchers wanting to work on frontier science in an international environment
- People not good at independent research and problem-solving
- Those seeking a stable 9-5 job rather than long-cycle projects
キャリア見通し
Junior researchers can advance to senior researcher or lab manager, some move to industry or academic professor roles, or enter regulatory bodies.
U.S. Bureau of Labor Statistics projects 10% employment growth from 2022-2032, much faster than average, driven by biotechnology and pharmaceuticals.
成長分野：
biotechnologypharmaceutical R&Dprecision medicineaging population
FAQ
データソース
Salary ranges are estimates aggregated from public listings on Indeed, Glassdoor, ERI SalaryExpert and the U.S. Bureau of Labor Statistics (BLS OEWS); employment and demand outlook cite the BLS Occupational Outlook and O*NET; visa and migration details follow the latest USCIS work-visa (H-1B / O-1 / L-1) and employment-based green-card (EB-2 / EB-3, incl. DOL PERM labor certification) rules. Figures are indicative only — always refer to the latest official sources.