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Data Science Postdoc Jobs in Colorado (NOW HIRING)

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Senior Quantum Scientist

Boulder, CO · On-site +1

Analyze experimental data, debug complex hardware/software interactions, and ensure reliability of ... While prior postdoctoral or industry experience is valuable, this role is also open to candidates ...

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Data Science Postdoc information

What is a data science postdoc?

A Data Science Postdoc is a temporary research position, typically at a university or research institution, for individuals who have recently completed a PhD. The role focuses on applying advanced data science techniques, such as machine learning, statistical modeling, and big data analysis, to solve complex research problems. Postdocs often work on interdisciplinary projects, collaborate with faculty, publish academic papers, and may also contribute to teaching. The goal is to build expertise, advance knowledge in a specific domain, and prepare for roles in academia, industry, or government.

What are typical daily or weekly responsibilities for a data science postdoc?

Data Science Postdocs often spend their days designing and conducting advanced data analyses, developing and testing predictive models, and communicating results through reports or academic publications. They frequently collaborate with faculty, graduate students, and industry partners on interdisciplinary projects, contributing their quantitative expertise. Additionally, Data Science Postdocs may mentor junior researchers, participate in lab meetings, present findings in seminars, and contribute to grant proposals. This dynamic environment provides opportunities to deepen research skills, publish impactful work, and prepare for future career advancement in academia or industry.

What are the key skills and qualifications needed to thrive in a data science postdoc position?

To thrive as a Data Science Postdoc, you need advanced analytical skills, expertise in statistical modeling, a doctoral degree in a quantitative field, and proven experience with data-driven research. Proficiency in programming languages like Python or R, along with experience using machine learning libraries, data visualization tools, and version control systems, is typically required. Excellent problem-solving abilities, collaborative teamwork, and effective communication skills help set outstanding candidates apart. These attributes are crucial for advancing knowledge, publishing impactful research, and working effectively within interdisciplinary research teams.

What are popular job titles related to Data Science Postdoc jobs in Colorado?

For Data Science Postdoc jobs in Colorado, the most frequently searched job titles are:

What job categories do people searching Data Science Postdoc jobs in Colorado look for?

The top searched job categories for Data Science Postdoc jobs in Colorado are:

Data Science Postdoc jobs near you
Infographic showing various Data Science Postdoc job openings in Colorado as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, 1% Temporary, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution.

Postdoctoral Researcher - Enzyme engineering for cell-free systems

National Renewable Energy Laboratory

Golden, CO • On-site

$76.60 - $126.40/hr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 5 days ago

Job description

Job Title

Postdoctoral Researcher – Enzyme Engineering for Cell‑Free Systems

Location

Golden, Colorado

Position Type

Postdoc (Fixed Term), 40 hours per week

Overview

RRES Center at NLR focuses on biological, chemical, and catalytic research in polymer design, upcycling, separations, synthetic biology, bioconversion, analytical sciences, computational modeling, and lignocellulosic chemistry. The successful candidate will work on the DOE‑funded project Integrating cell‑free systems and genome engineering to accelerate biosystems design for carbon‑negative biomanufacturing, developing optimized cell‑free systems for converting C1 substrates to sustainable biofuels and bioproducts.

Responsibilities
  • Identify, express, purify, and assay enzymes from full metabolic pathways.
  • Develop high‑throughput enzymatic assays to validate pathways.
  • Collaborate with data scientists to design efficient cell‑free production pathways.
  • Perform directed evolution, structure‑guided protein engineering, and machine‑learning‑guided protein engineering to improve enzyme and pathway function.
  • Conduct laboratory experiments safely and independently, with minimal supervision.
  • Plan and execute research in collaboration with multidisciplinary teams.
  • Communicate scientific results effectively in written and oral formats.
  • Author peer‑reviewed publications.
  • Work effectively in a large, multidisciplinary, multi‑institutional team of engineers and scientists.
Basic Qualifications
  • Recent PhD graduate within the last three years.
  • Experience with cloning, expression, and purification of proteins.
  • Experience with automation of biochemical assays.
  • Demonstrated experience in enzyme and/or protein engineering.
  • Ability to take initiative to set direction and goals for assigned tasks.
  • Strong troubleshooting and problem‑solving skills.
  • Strong record of quality peer‑reviewed publications.
  • Excellent safety record.
  • Ability to follow complex standard operating procedures with attention to detail.
Preferred Qualifications
  • Analytical chemistry experience with HPLC, GC‑FID, GC‑MS, and/or LC‑MS.
Annual Salary Range

$76,600 – $126,400

Benefits Summary
  • Medical, dental, and vision insurance.
  • Short‑term disability insurance.
  • Pension benefits.
  • 403(b) employee savings plan with employer match.
  • Life and accidental death and dismemberment insurance.
  • Personal time off and sick leave; paid holidays.
  • Possible performance‑, merit‑, and achievement‑based awards.
  • Possible relocation expense reimbursement.
Equal Opportunity Employer

All qualified applicants will receive consideration for employment without regard to age, color, disability, gender identity, genetic information, marital status, domestic partner status, military or veteran status, national origin, ancestry, race, religion, creed, sex, pregnancy, childbirth, breastfeeding, sexual orientation, or any other status protected by federal, state, or local law.

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