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Internship Machine Learning Neuroscience Jobs in Missouri

Post Doctoral Fellow

Saint Louis, MO · On-site

$47K - $64K/yr

... neuroscience, with opportunities for high-impact publications and grant development. Key ... Develop and apply statistical and machine-learning models (e.g., mixed-effects models, survival ...

... machine learning concepts. Important Information: - This is a freelance position compensated on an hourly basis. Please note that this is not an internship opportunity. - Candidates must be ...

AI Solutions Co-Op

Saint Louis, MO · On-site

$131K/yr

... or internships. * Strong written and verbal communication skills with the ability to translate ... Coursework, certifications, or hands-on experience in artificial intelligence, machine learning ...

Showing results 41-60

Internship Machine Learning Neuroscience information

What are the key skills and qualifications needed to thrive as an internship machine learning neuroscience, and why are they important?

To thrive in an Internship Machine Learning Neuroscience role, you generally need a background in neuroscience, computer science, or a related field, along with a solid understanding of machine learning concepts. Experience with programming languages such as Python, libraries like TensorFlow or PyTorch, and familiarity with neuroimaging software are commonly required. Strong analytical thinking, problem-solving skills, and effective communication help you work collaboratively and adapt to complex research environments. These skills are essential for contributing meaningfully to interdisciplinary projects at the intersection of neuroscience and artificial intelligence.

What is the difference between Internship Machine Learning Neuroscience vs Internship Data Science?

AspectInternship Machine Learning NeuroscienceInternship Data Science
Required CredentialsBackground in neuroscience, machine learning, programmingBackground in statistics, programming, data analysis
Work EnvironmentResearch labs, healthcare, academia, tech companiesBusiness, tech firms, research institutions
Industry UsageNeuroscience research, AI development, healthcare techBusiness analytics, product development, consulting

Internship Machine Learning Neuroscience focuses on applying machine learning techniques to neuroscience data, often within research or healthcare settings. In contrast, Internship Data Science covers a broader range of data analysis across industries. Both roles require programming skills, but the focus and industry applications differ significantly.

What is an internship in machine learning neuroscience?

An Internship in Machine Learning Neuroscience is a temporary position, often for students or recent graduates, that involves applying machine learning techniques to neuroscience research. Interns may work on projects such as analyzing brain imaging data, modeling neural networks, or developing algorithms to understand brain function. These internships provide hands-on experience in both computational methods and neuroscience concepts, helping interns build valuable skills for future academic or industry roles. Opportunities can be found in universities, research institutes, or technology companies with neuroscience divisions.

What types of projects do interns typically work on in a machine learning neuroscience internship?

Interns in Machine Learning Neuroscience often engage in projects that combine data analysis, algorithm development, and neuroscience research. This can include tasks such as preprocessing neural data, building and evaluating machine learning models to interpret brain signals, or developing tools for data visualization. Interns frequently collaborate with both data scientists and neuroscientists, gaining hands-on experience with real-world datasets and exposure to interdisciplinary research environments. These projects help interns build practical skills and contribute meaningful insights to ongoing research.
What are the most commonly searched types of Machine Learning Neuroscience jobs in Missouri? The most popular types of Machine Learning Neuroscience jobs in Missouri are:
What cities in Missouri are hiring for Internship Machine Learning Neuroscience jobs? Cities in Missouri with the most Internship Machine Learning Neuroscience job openings:

$47K - $64K/yr

Full-time

Re-posted 3 days ago


Saint Louis University rating

8.9

Company rating: 8.9 out of 10

Based on 12 frontline employees who took The Breakroom Quiz

34th of 617 rated colleges and universities


Job description

Who is Saint Louis University? Founded in 1818, Saint Louis University is one of the nation's oldest and most prestigious Catholic universities. SLU, which also has a campus in Madrid, Spain, is recognized for world-class academics, life-changing research, compassionate health care, and a strong commitment to faith and service.

Postdoctoral Fellow - Computational Biology / Bioinformatics

Focus:Multi-omics and Longitudinal Modeling in Alzheimer's Disease

Appointment:Full-time, 1-year term (renewable pending funding and performance)

Position Overview

We are seeking a highly motivated Postdoctoral Fellowwith a PhD in Computational Biology, Bioinformatics, Biostatistics, Data Science, or a related quantitative fieldto join an interdisciplinary research program focused on Alzheimer's disease (AD) and neurodegeneration.

The fellow will lead and contribute to advanced bioinformatics, multi-omics integration, and statistical modelingefforts using large, well-phenotyped longitudinal datasets(e.g., proteomics, transcriptomics, imaging, clinical, and biomarker data). The position is ideal for a candidate interested in mechanistic discovery, biomarker development, and translational neuroscience, with opportunities for high-impact publications and grant development.

Key Responsibilities

  • Perform computational analysis of large-scale omics datasets, including proteomics, transcriptomics, and related modalities

  • Integrate multi-omics datawith clinical, cognitive, and imaging phenotypes in longitudinal cohorts

  • Develop and apply statistical and machine-learning models(e.g., mixed-effects models, survival analysis, dimensionality reduction, clustering, trajectory modeling)

  • Lead reproducible analysis pipelinesin R, Python, or related frameworks

  • Interpret results in biological and clinical context, with emphasis on Alzheimer's disease mechanisms and biomarkers

  • Prepare figures, tables, and methods for peer-reviewed manuscriptsand conference presentations

  • Collaborate with clinicians, wet-lab scientists, and biostatisticians in an interdisciplinary environment

  • Contribute to grant proposalsand progress reports as appropriate

  • Mentor graduate or undergraduate trainees in computational methods (optional, depending on interest)

Required Qualifications

  • PhD in Computational Biology, Bioinformatics, Biostatistics, Data Science, Systems Biology, or a related quantitative discipline

  • Strong experience with high-dimensional biological data analysis

  • Proficiency in R and/or Pythonfor statistical computing and data analysis

  • Solid foundation in statistics and data modeling, particularly for longitudinal or cohort-based data

  • Demonstrated ability to work independently and manage complex datasets

  • Strong written and verbal communication skills in English

  • Evidence of productivity (e.g., peer-reviewed publications, preprints, or advanced projects)

Preferred Qualifications

  • Experience with longitudinal modeling(e.g., mixed-effects models, disease progression modeling)

  • Familiarity with neurodegenerative disease research, Alzheimer's disease, or aging biology

  • Experience with proteomics platforms(e.g., Olink, SomaScan, mass spectrometry)

  • Knowledge of multi-omics integration, network analysis, or pathway enrichment methods

  • Experience working with large consortium datasets(e.g., ADNI, AMP-AD, UK Biobank, similar)

  • Interest in translational research, biomarker discovery, or drug target identification

  • Experience with reproducible research practices (version control, documentation, workflow tools)

Environment & Opportunities

The fellow will join a highly collaborative research environment at the interface of neurology, neuroscience, and computational biology, with access to rich datasets and strong clinical context. The position offers:

  • Intellectual ownership of projects

  • Opportunities for first-author publications

  • Exposure to grant writing and translational research strategy

  • Career mentorship tailored to academic, industry, or hybrid career paths

Term & Compensation

  • One-year appointment with possibility of renewal based on funding and performance

  • Competitive salary and benefits commensurate with experience and institutional guidelines

Application Instructions:

Applicants should submit:

1) Curriculum vitae 2) Brief cover letter describing research interests and relevant experience 3) Contact information for 2-3 references

Grant-funded Post-Doctoral appointments may be terminated if grant funding ends.

This position does not currently sponsor J1, H1B, or O visas.

Function

Research Support

Scheduled Weekly Hours:

40

Saint Louis University is an equal opportunity/affirmative action employer. All qualified candidates will receive consideration for the position applied for without regard to race, color, religion, sex, age, national origin, disability, marital status, sexual orientation, military/veteran status, gender identity, or other non-merit factors. If accommodations are needed for completing the application and/or with the interviewing process, please contact Human Resources at 314-977-5847.


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