Postdoctoral Researcher

Overview

Role Purpose

Strategic Responsibilities

• Contribute to building machine learning models and computational strategy for therapeutic and functional genomics programs
• Build deep neural network-based models to ssupport data-driven decision making for target prioritization and validation
• Collaborate with wet lab teams to integrate experimental and computational workflows
• Identify and implement advanced bioinformatics tools and pipelines

Core Responsibilities

• Building machine learning models using multi-omics data for neuro-oncology projects
• Analyze RNA-seq, long-read sequencing (PacBio), and other omics datasets
• Develop and maintain bioinformatics pipelines for transcriptomics and genomics
• Perform differential expression, pathway analysis, and functional annotation
• Integrate multi-omics datasets (genomics, transcriptomics, proteomics where applicable)
• Support ASO target identification and validation through data-driven approaches
• Collaborate with lab scientists to interpret experimental results
• Maintain reproducible workflows (R/Python, workflow managers)
• Contribute to publications, grants, and scientific outputs
• Present findings internally and at scientific meetings
• Participate in teaching and education-related activities within the College of Medicine, MBRU.

Community Service

• Seeks and develops relationship with suitable external partners in order to raise the profile of the College and the University.
• Provides opportunities for assisting professional colleagues to maintain and enhance their skills by offering Continuing Professional development in their specialty.

Self-Management Responsibilities

• Defines performance goals at the start of the year in discussion with the reporting manager and ensures that the goals are monitored and achieved during the year.
• Takes ownership of his/her own learning agenda by identifying development needs in consultation with the reporting manager and working towards bridging the gaps through various means which go beyond just training.
• Understands the competencies relevant to his/her role and works towards displaying as well as developing these effectively.
• Keeps abreast of relevant professional/industry developments, new techniques and current issues through continued education and professional networks.

Minimum Qualifications

• PhD in Bioinformatics, Computational Biology, Genomics, or related field
• Strong experience in RNA-seq and transcriptomic data analysis
• Proficiency in R and/or Python
• Experience with NGS data analysis pipelines
• Ability to work independently and design computational workflows

Preferred Qualifications

• Experience with long-read sequencing (PacBio, Iso-Seq)
• Exposure to therapeutics, RNA biology, or functional genomics
• Familiarity with multi-omics integration
• Experience working with clinical or translational datasets
• Publication record in relevant field
• Written and spoken English is essential, Arabic is preferred
• Years of Experience:
• PhD in machine learning or artificial intelligence, bioinformatics, computational biology, genomics, or related field or a related field from an accredited institute/college/university.
• Minimum 1 – 2 years of relevant post-doctoral experience.