Transcriptomics Specialist / Instructor | Freelance/Contract Opportunity
SKI Plus International is seeking an experienced Transcriptomics Specialist / Instructor to join our academic training team on a freelance/contract basis.
We are developing an instructor-led professional training program focused on Transcriptomics and RNA-seq Data Analysis. We are looking for a highly skilled specialist with strong practical experience who can deliver comprehensive, hands-on training covering transcriptomics workflows from raw sequencing data through downstream analysis, visualization, biological interpretation, and reporting.
Key Responsibilities
The selected instructor will be responsible for:
- Delivering live online training sessions on transcriptomics and RNA-seq data analysis.
- Teaching complete transcriptomics workflows from raw sequencing reads to biological interpretation.
- Conducting hands-on practical sessions using real/public RNA-seq datasets.
- Teaching RNA-seq experimental design, sequencing concepts, library preparation considerations, and common sources of technical variation.
- Teaching raw-read quality control and preprocessing using tools such as FastQC, MultiQC, Cutadapt, Trimmomatic, and fastp.
- Demonstrating read alignment and mapping using tools such as STAR, HISAT2, and Salmon/Kallisto where appropriate.
- Teaching transcriptome quantification and gene/transcript-level abundance estimation.
- Working with common RNA-seq data formats including FASTQ, SAM/BAM, GTF/GFF, and count matrices.
- Teaching genome and transcriptome annotation concepts and the use of reference annotations.
- Conducting differential gene expression analysis using tools and frameworks such as DESeq2, edgeR, limma/voom, and related methods.
- Teaching normalization, dispersion estimation, statistical testing, multiple-testing correction, fold-change analysis, and interpretation of differentially expressed genes.
- Teaching exploratory analysis including PCA, hierarchical clustering, correlation analysis, heatmaps, and sample-level quality assessment.
- Teaching functional enrichment and pathway analysis using approaches/tools such as GO enrichment, KEGG, GSEA, clusterProfiler, g:Profiler, Enrichr, and related resources.
- Demonstrating transcriptomics visualization using tools such as R, Bioconductor, ggplot2, ComplexHeatmap, and IGV where appropriate.
- Introducing alternative splicing and transcript-level analysis, including tools such as rMATS, SUPPA, and related approaches.
- Introducing isoform/transcript quantification and analysis using appropriate tools and workflows.
- Teaching single-cell RNA-seq concepts and analysis where within the instructor's area of expertise, including commonly used frameworks such as Seurat and Scanpy.
- Where relevant, introducing specialized transcriptomics applications such as long-read transcriptomics, RNA-seq-based fusion detection, non-coding RNA analysis, and transcriptome assembly.
- Providing practical assignments and analysis exercises.
- Supervising and evaluating a final transcriptomics project.
- Answering students' technical questions and providing academic guidance throughout the training.
- Helping students interpret biological results and prepare professional-quality analysis reports.
Required Technical Expertise
Applicants should have strong hands-on experience across major transcriptomics/RNA-seq workflows and should be comfortable teaching commonly used tools and analytical approaches, including where relevant:
Quality Control & Preprocessing
- FastQC
- MultiQC
- fastp
- Cutadapt
- Trimmomatic
Alignment & Quantification
- STAR
- HISAT2
- Bowtie2 where applicable
- Salmon
- Kallisto
- featureCounts
- HTSeq
Transcriptome Assembly & Annotation
- StringTie
- Cufflinks/Cuffdiff or equivalent approaches
- GTF/GFF annotation
- Reference-guided and de novo transcriptome concepts
- Transcript/gene annotation resources
Differential Expression
- DESeq2
- edgeR
- limma/voom
- Bioconductor workflows
- Appropriate normalization and statistical methods
- Multiple-testing correction and FDR interpretation
Functional & Pathway Analysis
- Gene Ontology (GO)
- KEGG
- GSEA
- clusterProfiler
- g:Profiler
- Enrichr
- Pathway enrichment and biological interpretation
Visualization & Exploratory Analysis
- R
- Bioconductor
- ggplot2
- ComplexHeatmap
- PCA
- Heatmaps
- Hierarchical clustering
- IGV
Alternative Splicing & Isoform Analysis
- rMATS
- SUPPA
- Isoform-level analysis
- Transcript-level quantification
- Splicing event interpretation
Single-Cell Transcriptomics
Knowledge of commonly used single-cell RNA-seq workflows and tools such as:
- Seurat
- Scanpy
- Cell Ranger
- Quality control and filtering
- Normalization
- Dimensionality reduction
- Clustering
- Marker-gene analysis
- Cell-type annotation
- Differential expression in single-cell datasets
Additional Transcriptomics Expertise
Experience with one or more of the following is highly desirable:
- Long-read RNA sequencing/transcriptomics
- Nanopore/PacBio transcriptomics
- De novo transcriptome assembly
- RNA-seq fusion detection
- Non-coding RNA analysis
- miRNA/small RNA analysis
- Spatial transcriptomics
- Time-series transcriptomics
- Multi-omics integration
- Public transcriptomics repositories such as GEO, SRA, and ENA
Other Technical Requirements
- Strong command of Linux/Unix and command-line environments.
- Strong proficiency in R/Bioconductor for transcriptomics analysis.
- Familiarity with Python-based transcriptomics workflows is desirable.
- Ability to work with large biological datasets.
- Ability to troubleshoot common bioinformatics/software issues.
- Strong understanding of experimental design and statistical principles relevant to RNA-seq analysis.
- Ability to explain computational concepts clearly to students with different levels of prior experience.
Preferred Qualifications
- MSc/MPhil/PhD in Bioinformatics, Biotechnology, Computational Biology, Genomics, Genetics, Molecular Biology, or a related field.
- Demonstrable research experience involving transcriptomics/RNA-seq.
- Publications or research projects involving transcriptomic data analysis are highly desirable.
- Previous experience in teaching, mentoring, workshops, or professional training is preferred.
- Experience designing complete RNA-seq/transcriptomics analysis pipelines is highly desirable.
Engagement & Payment — Please Read Carefully
This is a freelance/contract-based instructional opportunity, not a permanent or salaried employment position.
The instructor will be engaged on a per-training-cohort basis.
- The training will be delivered online.
- Each training cohort is expected to run for approximately 3–4 weeks.
- A cohort will be formally confirmed once the required minimum number of students has enrolled.
- Teaching will not be expected to begin before the cohort is officially confirmed.
- Compensation will be mutually agreed upon with the selected instructor before any teaching work begins.
- Payment will be made according to the mutually agreed payment schedule for the confirmed cohort.
- The instructor will not be expected to conduct unpaid classes before the cohort is confirmed.
- There is no guaranteed number of future cohorts or students.
- Any subsequent cohort will be subject to mutual confirmation between SKI Plus International and the instructor.
- The teaching schedule, scope of work, compensation, and payment terms will be clearly agreed upon in writing before the instructor begins the engagement.
This structure is intended to ensure clear expectations and transparent terms for both SKI Plus International and the selected instructor.
Work Mode
Fully Remote — Candidates from anywhere in Pakistan are welcome to apply.
How to Apply
Please submit:
1. An updated CV.
2. A brief summary of your transcriptomics/RNA-seq experience.
3. A list of transcriptomics tools, pipelines, and frameworks in which you have genuine hands-on experience.
4. Examples of transcriptomics/RNA-seq projects, research work, publications, or datasets you have worked with, where applicable.
5. Previous teaching, training, mentoring, or workshop experience, if applicable.
6. Your expected compensation for delivering a 3–4 week transcriptomics training cohort.
Applicants should apply only if they have genuine hands-on transcriptomics/RNA-seq experience and can independently demonstrate, explain, and troubleshoot the relevant workflows for learners.
SKI Plus International
Academic Training • Professional Skills • Research & Learning