1

Chemistry Data Science Internship Jobs in Appleton, WI

... clinical data sources. * Provide expert insights on structure-activity and structure-property ... Assess and review AI-generated outputs for scientific rigor, accuracy, and practical relevance ...

The Lab Scientist owns key analytical instrumentation, leads method development, manages data ... Graduate degree in Chemistry, Materials Science, or Engineering with 5+ years related experience ...

The Lab Scientist owns key analytical instrumentation, leads method development, manages data ... Graduate degree in Chemistry, Materials Science, or Engineering with 5+ years related experience ...

Take appropriate action based on the data collected. * Analytical chemistry routine testing and ... College degree in Science (Microbiology, Biology, Chemistry, Food Science). * Working brewing ...

Quality Assurance

Green Bay, WI · On-site

$20 - $24/hr

Take appropriate action based on the data collected. * Analytical chemistry routine testing and ... College degree in Science (Microbiology, Biology, Chemistry, Food Science). * Working brewing ...

Take appropriate action based on the data collected. * Analytical chemistry routine testing and ... College degree in Science (Microbiology, Biology, Chemistry, Food Science). * Working brewing ...

Showing results 21-40

Chemistry Data Science Internship information

See Appleton, WI salary details

$11

$21

$41

How much do chemistry data science internship jobs pay per hour?

As of Aug 20, 2026, the average hourly pay for chemistry data science internship in Appleton, WI is $21.96, according to ZipRecruiter salary data. Most workers in this role earn between $16.88 and $23.94 per hour, depending on experience, location, and employer.

What is a chemistry data science internship?

A Chemistry Data Science Internship is a temporary position designed for students or recent graduates to gain practical experience at the intersection of chemistry and data science. Interns typically work on projects involving the analysis of chemical data, application of machine learning techniques to chemical problems, and development of software tools to aid research. This role helps interns develop skills in programming, statistics, and scientific research, while contributing to advancements in areas like drug discovery, materials science, or environmental chemistry. The internship provides valuable hands-on experience and often serves as a stepping stone to careers in research, industry, or academia.

What types of projects and responsibilities can I expect during a chemistry data science internship?

As a Chemistry Data Science Intern, you can expect to work on projects that combine chemical research with advanced data analysis techniques. Typical responsibilities include cleaning and analyzing large datasets from laboratory experiments or chemical databases, developing predictive models to understand chemical properties or reactions, and visualizing results to support research findings. You may also collaborate with chemists, data scientists, and software engineers, contributing to interdisciplinary teams on tasks such as automating data collection or optimizing experimental design. This hands-on experience helps develop both your scientific and computational skills, preparing you for future roles in research or industry.

What are the key skills and qualifications needed to thrive as a chemistry data science intern, and why are they important?

To thrive as a Chemistry Data Science Intern, you need a solid background in chemistry, statistics, and data analysis, often supported by ongoing or completed coursework in chemistry and data science. Familiarity with programming languages like Python or R, data visualization tools, and experience using cheminformatics software are highly valuable. Strong problem-solving, attention to detail, and effective communication skills help interns draw actionable insights and collaborate with multidisciplinary teams. These skills are essential for turning complex chemical data into meaningful conclusions that advance research and innovation.

What is the difference between Chemistry Data Science Internship vs Chemistry Data Analyst?

AspectChemistry Data Science InternshipChemistry Data Analyst
Required CredentialsUndergraduate or graduate degree in chemistry, data science, or related fieldsBachelor's degree in chemistry, data analysis, or related fields
Work EnvironmentResearch labs, corporate R&D, or academic settingsCorporate, laboratory, or research environments
Industry UsageUsed for training, skill development, and project workUsed for interpreting data, reporting, and decision-making

The Chemistry Data Science Internship focuses on training and skill development in applying data science techniques to chemistry problems, often for students or early-career professionals. In contrast, the Chemistry Data Analyst role involves analyzing chemical data to support research or business decisions, typically requiring more experience. Both roles are common in research and industry, but internships are more educational, while analyst positions are more operational.

What cities near Appleton, WI are hiring for Chemistry Data Science Internship jobs?

Cities near Appleton, WI with the most Chemistry Data Science Internship job openings:

Infographic showing various Chemistry Data Science Internship job openings in Appleton, WI as of July 2026, with employment types broken down into 1% As Needed, 79% Full Time, 13% Part Time, and 7% Contract. Highlights an 81% Physical, 3% Hybrid, and 16% Remote job distribution, with an average salary of $45,673 per year, or $22 per hour.

Bioinformatics Software Engineer

micro1 AI

Green Bay, WI • Remote

$80 - $110/hr

Part-time

Posted 17 days ago


Job description

Role Title: Computational Biology & Cheminformatics Expert


Role Type: Contractor


Location: Remote


micro1 is engaging Computational Biology & Cheminformatics Experts to contribute their expertise to a customer’s computational drug discovery project. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.


Scope of Work

  1. Analyze and interpret small-molecule and drug discovery datasets using advanced computational biology, bioinformatics, and cheminformatics methods.
  2. Curate, annotate, and validate chemical and biological datasets (e.g., ChEMBL, PubChem, DrugBank) to support AI-driven discovery platforms.
  3. Evaluate compound-target interactions, ADMET properties, and lead optimization strategies by integrating chemical, biological, and clinical data sources.
  4. Provide expert insights on structure-activity and structure-property relationships (SAR/SPR), medicinal chemistry approaches, and experimental design considerations.
  5. Build and implement code-based benchmark tasks (e.g., terminal/CLI-based environments) that reflect realistic computational drug discovery scenarios.
  6. Develop reproducible environments (e.g., using Docker) and automated testing pipelines to ensure task correctness and solvability.
  7. Assess and review AI-generated outputs for scientific rigor, accuracy, and practical relevance, delivering detailed written feedback and recommendations.


Preferred Qualifications

  1. Advanced expertise in Computational Biology, Cheminformatics, Medicinal Chemistry, Biochemistry, or related fields; advanced degree (PhD, MSc, PharmD) highly valued but not strictly required.
  2. Strong coding proficiency in Python (beyond analysis scripts), with hands-on experience building tools, pipelines, or testable code; familiarity with Git, GitHub, and Docker.
  3. Extensive experience with cheminformatics toolkits and platforms such as RDKit, KNIME, Schrödinger, OpenEye, or MOE.
  4. Proven track record in small-molecule drug discovery, SAR/QSAR evaluation, ADMET prediction, or virtual screening workflows.
  5. Comfort working with public chemical and bioactivity databases and integrating diverse datasets for scientific analysis.
  6. Demonstrated ability to clearly communicate complex chemical and biological concepts in written feedback and reports.
  7. Experience participating in multidisciplinary and/or remote projects; familiarity with AI-assisted coding tools is a plus.