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Remote Computational Materials Science Jobs in Wisconsin

Physical Chemistry Tutor

Madison, WI ยท Remote

$18 - $40/hr

Emphasizes mathematical rigor in chemical reasoning and connects physical chemistry to materials science, nanotechnology, and computational chemistry applications. * Curriculum Awareness & Adaptive ...

Physical Chemistry Tutor

Milwaukee, WI ยท Remote

$18 - $40/hr

Emphasizes mathematical rigor in chemical reasoning and connects physical chemistry to materials science, nanotechnology, and computational chemistry applications. * Curriculum Awareness & Adaptive ...

Bioinformatics Scientist Role Type: Contractor Location: Remote micro1 is engaging Bioinformatics ... Advanced degree (e.g., PhD or MSc) in Bioinformatics, Computational Biology, Medicinal Chemistry ...

Bioinformatics Scientist Role Type: Contractor Location: Remote micro1 is engaging Bioinformatics ... Advanced degree (e.g., PhD or MSc) in Bioinformatics, Computational Biology, Medicinal Chemistry ...

Bioinformatics Scientist Role Type: Contractor Location: Remote micro1 is engaging Bioinformatics ... Advanced degree (e.g., PhD or MSc) in Bioinformatics, Computational Biology, Medicinal Chemistry ...

Bioinformatics Scientist Role Type: Contractor Location: Remote micro1 is engaging Bioinformatics ... Advanced degree (e.g., PhD or MSc) in Bioinformatics, Computational Biology, Medicinal Chemistry ...

Showing results 21-40

Remote Computational Materials Science information

What is remote computational materials science?

Remote computational materials science involves using computer simulations and modeling techniques to study and design materials, all while working from a remote location rather than in a physical lab. Researchers in this field use software tools to predict the properties and behaviors of materials at the atomic or molecular level, which can accelerate the discovery of new materials for applications in energy, electronics, and manufacturing. Remote computational materials scientists commonly collaborate with teams online, analyze data, and run simulations on high-performance computing systems accessible via the internet.

What are some common challenges faced when working remotely in computational materials science, and how can they be addressed?

Remote computational materials scientists often encounter challenges such as coordinating with interdisciplinary teams across different time zones and ensuring efficient access to high-performance computing resources. Clear communication through regular virtual meetings and collaborative platforms helps maintain project alignment. Additionally, staying organized with version control systems and thorough documentation is essential for seamless teamwork. Being proactive about addressing technical issues, such as software compatibility or data transfer limitations, also ensures productivity.

What is the difference between Remote Computational Materials Science vs Remote Materials Data Analyst?

AspectRemote Computational Materials ScienceRemote Materials Data Analyst
Required CredentialsAdvanced degrees in materials science, physics, or chemistry; experience with computational modelingBachelor's or master's in data science, materials science, or related fields; proficiency in data analysis tools
Work EnvironmentResearch-focused, using simulation software and programmingData processing, visualization, and reporting using analytics platforms
Employer & Industry UsageResearch institutions, R&D departments in manufacturing, tech companiesManufacturers, consulting firms, research labs analyzing material data

Remote Computational Materials Science involves simulating and modeling materials at the atomic or molecular level, requiring programming and scientific expertise. In contrast, Remote Materials Data Analysts focus on analyzing existing material data to inform decisions, emphasizing data skills. Both roles are essential in materials research but differ in their core activities and skill sets.

What are the key skills and qualifications needed to thrive as a remote computational materials scientist, and why are they important?

To thrive as a Remote Computational Materials Scientist, you need a strong background in materials science, physics, or chemistry, often with a PhD or advanced degree, and expertise in computational modeling. Familiarity with simulation software like VASP, Quantum ESPRESSO, or LAMMPS, as well as proficiency in programming languages such as Python or Fortran, is typically required. Excellent problem-solving skills, self-motivation, and clear written communication are crucial for collaborating remotely and conveying complex results. These competencies enable effective independent research, accurate data analysis, and seamless teamwork in a virtual scientific environment.
What are popular job titles related to Remote Computational Materials Science jobs in Wisconsin? For Remote Computational Materials Science jobs in Wisconsin, the most frequently searched job titles are:
What job categories do people searching Remote Computational Materials Science jobs in Wisconsin look for? The top searched job categories for Remote Computational Materials Science jobs in Wisconsin are:
What cities in Wisconsin are hiring for Remote Computational Materials Science jobs? Cities in Wisconsin with the most Remote Computational Materials Science job openings:

Bioinformatics Research Scientist - AI Reviewer

micro1 AI

Milwaukee, WI โ€ข Remote

$80 - $110/hr

Part-time

Posted 9 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 customerโ€™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 โ€” 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, Schrรถdinger, 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.