Entry Level Research Assistant Machine Learning Jobs

SUMMARY:
The Research Assistant supports laboratory-based brain tumor research within the Department of Neurosurgery by conducting statistical programming, multi-omics and epigenetic data analysis, computational analysis and machine learning of human and patient-derived cells, tissues, images and analyzing their responses to drug and radiation treatments. The role includes performing statistical analysis, transcriptomic analysis, stochastic or mechanistic simulation modeling, computational imaging analysis, machine learning, and prepare figures, technical reports, and manuscripts for publication and presentation. This position exists to advance ongoing funded research by analyzing experimental and clinical data and supporting the laboratory’s scientific and scholarly activities.

Brown University Health employees are expected to successfully role model the organization's values of Compassion, Accountability, Respect, and Excellence as these values guide our everyday actions with patients, customers and one another.
In addition to our values, all employees are expected to demonstrate the core Success Factors which tell us how we work together and how we get things done. The core Success Factors include:
Instill Trust and Value Differences
Patient and Community Focus and Collaborate
RESPONSIBILITIES:

Conduct laboratory research activities involving human and patient-derived cell cultures to support ongoing neuroscience and brain tumor studies.

Perform experimental procedures using microscopic imaging, proliferation, and migration assays to generate data for biomedical research projects.

Prepare biological samples and execute molecular analyses, including immunostaining, western blotting, and RNA sequencing workflows.

Apply statistical, computational and bioinformatic methods to analyze experimental and clinical datasets related to cell growth, treatment response, and gene expression.

Perform bulk and single-cell RNA-seq and analysis.

Perform spatial transcriptomic analysis.

Develop and apply stochastic and mechanistic modeling.

Develop and apply machine learning tools to analysis genomic and MRI datasets. Assist in the design and implementation of computational and experimental protocols to support laboratory research objectives and funded study aims.

Maintain laboratory materials, biomaterials, and substrates to ensure readiness for experimental use and research continuity.

Participate in departmental and academic research activities to contribute to collaborative scientific initiatives within Neurosurgery and affiliated programs.

Performs other duties as assigned.

MINIMUM QUALIFICATIONS:
BASIC KNOWLEDGE:

Minimum qualifications include a Bachelor’s degree in Biology, Biophysics, Biomedical Engineering, Bioinformatics, Statistics, Computer Science, or a related field. A Master’s degree or equivalent advanced training in a relevant discipline may also be considered. No specific licensure, registration, or professional certification is required for this position.

EXPERIENCE:

Candidates should have at least two years of relevant laboratory research experience in a biomedical, biological sciences, or related research environment, which may include academic laboratory training obtained during undergraduate or graduate study. Experience should include hands-on work with cell culture techniques, basic molecular or imaging assays, statistical and bioinformatic analysis, machine learning or computational modeling. Applicants must demonstrate the ability to follow and execute experimental and computational protocols, maintain accurate research documentation, and communicate effectively in English, both orally and in writing. Basic computational, statistical, or programming skills, along with the ability to work collaboratively in a research team environment, are required.

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EEO Statement:

Brown University Health is committed to providing equal employment opportunities and maintaining a work environment free from all forms of unlawful discrimination and harassment.

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