Distinguished Data Analyst for Neurological Disorders

Há 4 dias

Rio de Janeiro, Rio de Janeiro, Brasil beBeeNeurodegeneration Tempo inteiro
Research Fellow - Neurodegeneration and Computational Research

This role supports the development of computational skills in neuroscience research.

The fellow will contribute to analyzing datasets related to neurodegenerative diseases, advancing the understanding of disease mechanisms.

This position has no supervisory authority. The fellow will work directly under the supervision of a principal investigator or mentor in a host lab affiliated with the NDCF program.

Nature and Scope:

The fellow will engage in interdisciplinary research within a host lab at Howard University or a partner institution, focusing on computational approaches to neurodegeneration.

  • Gain hands-on experience analyzing neurophysiological, genomic, or imaging data using tools like Python, R, or machine learning frameworks.
  • Collaborate with researchers, other fellows, and faculty, participating in lab meetings and NDCF symposia.
Accountabilities:
  1. Assist in analyzing datasets (e.g., MRI, genomic, or microbiome data) using computational tools under the guidance of a mentor, identifying patterns or biomarkers in neurodegenerative diseases.
  2. Learn and apply statistical or machine learning methods to support research on disease mechanisms, following lab protocols.
  3. Support data processing tasks, such as image analysis or sequence alignment, using provided software or scripts.
  4. Prepare research summaries and present findings at NDCF symposia, lab meetings, or external conferences.
  5. Contribute to team discussions, collaborating with lab members to integrate computational and experimental findings.
Core Competencies:
  • Computational Aptitude: Familiarity with programming (e.g., Python, R) or data analysis tools, with a strong interest in learning advanced computational techniques.
  • Analytical Thinking: Ability to approach complex datasets with curiosity and apply structured methods to derive meaningful insights under mentorship.
  • Collaboration: Strong interpersonal skills to work effectively in interdisciplinary teams, including researchers, students, and faculty.
  • Communication: Clear written and verbal communication to present research progress and engage with scientific audiences.
  • Adaptability: Eagerness to acquire new skills and adapt to evolving research tools and methodologies in a training-focused environment.
Minimum Requirements:
  • Education: Bachelor's or Master's degree in neuroscience, biology, computer science, bioinformatics, or a related field.
  • Experience: Some exposure to programming, data analysis, or neuroscience research through coursework, internships, or personal projects.
  • Skills: Basic familiarity with computational tools (e.g., Python, R, MATLAB, or command-line interfaces) or a strong interest in learning these skills.

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