Research Specialist I

JOB SUMMARY

The Research Specialist I performs routine and moderately complex scientific laboratory technical work, selecting and applying laboratory procedures and techniques to assignments with clear, specific objectives. Assignments may require investigation of a number of variables and complex features. He/she works with general supervision. The incumbent is required to exercise judgment in making technical decisions related to delegated tasks and escalating complex issues.

KEY ROLE ACCOUNTABILITIES

• Contributes to the delivery of departmental goals, through personal effort in own work area.
• Makes recommendations to the Investigator regarding improvements in methods and processes.
• Works under general supervision, performs all routine lab procedures, and associated responsibilities, as dictated by the workload in the rostered area.
• Solves moderately complex problems and performs a specific variety of technical assignments within broader projects.
• Modifies practices and techniques in routine situations to perform duties, adjusts and correlates data, recognizes discrepancies in results.
• Contributes to ongoing research projects in the laboratory that include taking measurements and recording observations, collecting, compiling and processing data.
• Assists in procurement of additional/new funding through contributions to technical proposal preparation and/or presentations.
• Trains junior lab technical staff in basics of research workflow.
• Adheres to lab SOPs and performs quality control checks.
• Stays current with literature in ongoing and proposed research projects.
• Assesses lab inventory and orders supplies when needed.
• Presents novel research and techniques to research group.
• Adheres to Sidra’s standards as they appear in the Code of Conduct and Conflict of Interest policies
• Adheres to and promotes Sidra’s Values

In view of the evolving needs and opportunities within Sidra, this position may be required to perform other duties as assigned and reporting relationships may vary.

QUALIFICATIONS, EXPERIENCE AND SKILLS – SELECTION CRITERIA

Education

Bachelor’s degree in bioinformatics, computational biology, computer science, Software Engineering or relevant field.

Experience

3+ years of experience in research laboratory environment or 1 year of work experience in Sidra.

Exceptions to the experience requirement may be granted for Qatari nationals (internal and external candidates), with a reduction of up to two (2) years.

Job Specific Skills and Abilities.

Essential

• Proficiency in programming languages such as Python, R, C++, or Java

• Basic Knowledge of SQL/NoSQL databases (e.g., MySQL, PostgreSQL, MongoDB).

• Basic Knowledge database querying, optimization, and API integration

• Knowledge in developing user-friendly interfaces with HTML, CSS, JavaScript, and front-end frameworks (e.g., React, Shiny, Quarto)

• Familiarity with dynamic data visualization tools (e.g., Plotly, ggplot2)

• Solid knowledge in Linux/Unix environments and command-line tools

• Proficiency with version control systems (e.g., Gitlab, Github).

• Familiarity with bioinformatics tools (e.g., BWA, GATK, STAR) and biological databases (e.g., Ensembl, NCBI).

• Demonstrated functional knowledge and laboratory experience in relevant field.

• Evidence of ongoing continual development and personal development.

• Demonstrated functional knowledge and laboratory experience in relevant field.
• Evidence of ongoing continual development and personal development.
• Demonstrated strong analytical, problem solving and decision-making skills.
• Demonstrated knowledge and understanding of biomedical research, research equipment and environmental safety and accident prevention measures.
• Demonstrated excellent communication and interpersonal skills.
• Excellent organizational skills.
• Proficiency with Microsoft Office suite.

• Fluency in written and spoken English .
  

Preferred

Basic Knowledge of workflow management systems (e.g., Snake make, Next flow, or CWL)

Familiarity with high-performance computing (HPC) environments and job schedulers (e.g., LSF, Slurm)

Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud) and containerization tools (e.g., Docker, Singularity)

Exposure to machine learning and data science frameworks (e.g., TensorFlow, Scikit-Learn)