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Remote Data Science Neuroscience Jobs in Portland, OR

micro1 AI

AI Trainer - Microbiology Expert

Gresham, OR · Remote

$70 - $90/hr

Remote micro1 is engaging Microbiologists to contribute their scientific expertise to a unique ... Document experimental findings and processes with a focus on clarity for AI training data.

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Remote Data Science Neuroscience information

See Portland, OR salary details

$44K

$151.1K

$213.2K

How much do remote data science neuroscience jobs pay per year?

As of Aug 15, 2026, the average yearly pay for remote data science neuroscience in Portland, OR is $151,080.00, according to ZipRecruiter salary data. Most workers in this role earn between $125,700.00 and $176,600.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a remote data science neuroscience professional?

To thrive as a Remote Data Science Neuroscience professional, you need a background in neuroscience and statistics, strong programming skills (especially in Python or R), and experience with data analysis techniques. Familiarity with tools such as machine learning frameworks (e.g., TensorFlow or scikit-learn), neuroimaging software (like SPM or FSL), and cloud-based collaboration platforms is typically required. Exceptional problem-solving, communication, and self-motivation are crucial for effectively working with interdisciplinary teams in a remote setting. These skills and qualities ensure accurate data interpretation, effective research collaboration, and successful project delivery in a complex and evolving field.

How do remote data science neuroscience professionals typically collaborate with multidisciplinary teams?

Remote data science professionals in neuroscience often work closely with neuroscientists, clinicians, and software engineers, using digital tools to facilitate communication and project management. Collaboration usually occurs through regular virtual meetings, shared data repositories, and collaborative coding platforms. This setup requires strong communication skills and the ability to translate complex analytical findings into actionable insights for team members from diverse backgrounds. Building strong virtual relationships and maintaining clear documentation are key to ensuring project success and smooth cross-functional collaboration.

What is a remote data science neuroscience?

A Remote Data Science Neuroscience job involves using data science techniques, such as machine learning and statistical analysis, to interpret and analyze neuroscience data while working from a remote location. Professionals in this role typically work with large datasets from brain imaging, electrophysiology, or behavioral studies to uncover insights about brain function and neurological diseases. These positions require strong programming skills, knowledge of neuroscience concepts, and the ability to collaborate virtually with research teams. The remote aspect allows for flexibility in work location, making it accessible to a broader range of candidates.

What are the most commonly searched types of Data Science Neuroscience jobs in Portland, OR?

The most popular types of Data Science Neuroscience jobs in Portland, OR are:

What are popular job titles related to Remote Data Science Neuroscience jobs in Portland, OR?

For Remote Data Science Neuroscience jobs in Portland, OR, the most frequently searched job titles are:

What job categories do people searching Remote Data Science Neuroscience jobs in Portland, OR look for?

The top searched job categories for Remote Data Science Neuroscience jobs in Portland, OR are:

Remote Data Science Neuroscience jobs near you

Bioinformatics Research Scientist - AI Reviewer

micro1 AI

Vancouver, WA • Remote

$80 - $110/hr

Part-time

Posted 12 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.

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