# Nanotechnology Engineering Technologists and Technicians

> Implement production processes and operate commercial-scale production equipment to produce, test, or modify materials, devices, or systems of unique molecular or macromolecular composition. Operate advanced microscopy equipment to manipulate nanoscale objects. Work under the supervision of nanoengineering staff.

- **SOC code:** 17-3026.01
- **Canonical URL:** https://singulariki.com/roles/role-17-3026-01
- **Also known as:** Nanofabrication Specialist, Process Engineering Technician (Process Engineering Tech), R and D Engineer (Research and Development Engineer), Research Lab Associate (Research Laboratory Associate), Engineering Technician (Engineering Tech), Lab Technician (Laboratory Technician), Research Scientist, Research Specialist
- **Frame:** "AI exposure" means task overlap (how codifiable the work is), not jobs lost or a forecast. Every figure below is traced to a named public dataset.

## What this work is

**Core tasks** (O*NET):
- Produce images or measurements, using tools or techniques such as atomic force microscopy, scanning electron microscopy, optical microscopy, particle size analysis, or zeta potential analysis.
- Maintain accurate record or batch-record documentation of nanoproduction.
- Calibrate nanotechnology equipment, such as weighing, testing, or production equipment.
- Maintain work area according to cleanroom or other processing standards.
- Repair nanotechnology processing or testing equipment or submit work orders for equipment repair.
- Collaborate with scientists or engineers to design or conduct experiments for the development of nanotechnology materials, components, devices, or systems.
- Assist nanoscientists or engineers in processing or characterizing materials according to physical or chemical properties.
- Operate nanotechnology compounding, testing, processing, or production equipment in accordance with appropriate standard operating procedures, good manufacturing practices, hazardous material restrictions, or health and safety requirements.
- Monitor equipment during operation to ensure adherence to specifications for characteristics such as pressure, temperature, or flow.
- Monitor hazardous waste cleanup procedures to ensure proper application of nanocomposites or accomplishment of objectives.
- Measure or mix chemicals or compounds in accordance with detailed instructions or formulas.
- Inspect or measure thin films of carbon nanotubes, polymers, or inorganic coatings, using a variety of techniques or analytical tools.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Engineering and Technology _(knowledge)_
- Written Comprehension _(ability)_
- English Language _(knowledge)_
- Reading Comprehension _(essential_skill)_
- Oral Comprehension _(ability)_
- Computers and Electronics _(knowledge)_
- Chemistry _(knowledge)_
- Critical Thinking _(essential_skill)_
- Problem Sensitivity _(ability)_
- Deductive Reasoning _(ability)_
- Oral Expression _(ability)_
- Written Expression _(ability)_

**Skills in demand:**
- English Language _(Common Skill)_
- Reading Comprehension _(Common Skill)_
- Chemistry _(Specialized Skill)_
- Deductive Reasoning _(Common Skill)_
- Critical Thinking _(Common Skill)_
- Information Ordering _(Specialized Skill)_
- Inductive Reasoning _(Common Skill)_
- Mathematics _(Common Skill)_
- Writing _(Common Skill)_
- Physics _(Specialized Skill)_
- Complex Problem Solving _(Common Skill)_
- Active Listening _(Common Skill)_

**Tools & technology:**
- Microsoft Access _(hot technology)_
- Microsoft Excel _(hot technology)_
- Microsoft Office software _(hot technology)_
- Microsoft PowerPoint _(hot technology)_
- Microsoft Windows _(hot technology)_
- Microsoft Word _(hot technology)_
- Image analysis software
- Optical imaging systems
- Simulation software
- SPMLab

## AI exposure & outlook

- **AI task-overlap index:** 55th percentile (Moderate) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 62nd percentile (Moderate) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 46th percentile (Moderate) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 60th percentile (Moderate) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 19th percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** no — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** 1.7% growth (About average); 6.3k annual openings; 74.6k → 75.9k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $64,790; 73,410 employed.

## Sources

- **O*NET** (30.3) — U.S. Department of Labor / National Center for O*NET Development. https://www.onetcenter.org/database.html
- **BLS Occupational Employment and Wage Statistics (OEWS)** (May 2024) — U.S. Bureau of Labor Statistics. https://www.bls.gov/oes/
- **BLS Employment Projections** (2024–2034) — U.S. Bureau of Labor Statistics. https://www.bls.gov/emp/
- **Anthropic Economic Index** (v4 (2026-01-15) + v2 (2025-03-27)) — Anthropic. https://www.anthropic.com/economic-index
- **Microsoft “Working with AI”** (working-with-ai) — Microsoft Research. https://www.microsoft.com/en-us/research/
- **“GPTs are GPTs” (Eloundou et al.)** (arXiv 2303.10130) — OpenAI / academic. https://arxiv.org/abs/2303.10130
- **AI Occupational Exposure (AIOE)** (Felten, Raj & Seamans) — academic. https://github.com/AIOE-Data/AIOE
- **Frey & Osborne (2013)** (frey-osborne-automation) — academic. https://www.oxfordmartin.ox.ac.uk/publications/the-future-of-employment/
- **Dingel & Neiman (2020)** (dingel-neiman-workathome) — academic. https://github.com/jdingel/DingelNeiman-workathome

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_Generated from Singulariki's joined dataset; data snapshot 2026-06-02T21:00:32.945303+00:00. https://singulariki.com/roles/role-17-3026-01_