Job Summary

Biotecnika is hiring a Trainer & Scientist to design and deliver AI/ML training in cancer genomics and computational biology, from raw biological data to ML modelling and interpretation. You will build curriculum, teach live batches and mentor learners on hands-on projects. Bangalore-based hybrid role, full-time, salary as per market standards.

Job Title: Trainer & Scientist – AI/ML, Cancer Genomics & Computational Biology

Company: Biotecnika Info Labs Pvt. Ltd.

Location: Bangalore (Hybrid: first half at our Bangalore office, second half online)

Employment Type: Full-time

Experience: M.Sc. / M.Tech: 4–5 years | Ph.D.: 2 years (relevant research, industry or teaching experience)

Qualification: M.Sc. / M.Tech / Ph.D. in Bioinformatics, Biotechnology, Computational Biology, Data Science or a related field

Salary: As per market standards

About Biotecnika

Founded in 2006, Biotecnika is one of India's largest biosciences career and education platforms, helping life science professionals build strong careers through training, certifications, placement support and career guidance. Our five brands (Biotecnika India, Rasayanika, Pharmanika, Meditechnika and Biotecnika Global) reach learners across India and worldwide.

About the Role

Biotecnika is looking for a Trainer & Scientist who combines AI/ML expertise with life sciences research. You will design and deliver beginner-to-advanced training programs that take learners through the full pipeline, from raw biological data processing to ML modelling and biological interpretation, with a focus on cancer genomics and drug discovery.

Key Responsibilities

- Develop curriculum and training content in AI/ML for life sciences,



cancer genomics and computational biology
- Deliver live online/offline training sessions and workshops
- Guide students through hands-on projects in genomics, cheminformatics and multi-omics
- Mentor learners and review their projects and capstones
- Keep content current with emerging tools, including LLM workflows and agentic AI

Must-Have Skills

- AI/ML in life sciences: Regression, classification (Random Forest, SVM), clustering; CNNs, RNNs/LSTMs, Transformers; PCA, t-SNE, UMAP; model evaluation (Precision, Recall, F1-score, ROC-AUC, cross-validation).
- Cancer genomics: Tumor classification, biomarker discovery, multi-omics integration, subtype and prognosis modelling.
- Coding: Python (Pandas, NumPy, Scikit-learn, TensorFlow/Keras, Biopython), R (Tidyverse, ggplot2, Bioconductor), Linux/Bash, Jupyter/Colab, GitHub.
- Biostatistics: Hypothesis testing, confidence intervals, t-test, ANOVA, chi-square, regression, study design.
- Proven teaching, training or mentoring ability.

Solid Preference (any of these)

- NGS & multi-omics: FastQC/MultiQC, BWA, Bowtie2, GATK, VEP; RNA-Seq (STAR, HISAT2, featureCounts, DESeq2, edgeR); Scanpy/Seurat; QIIME2, Kraken2; ChIP-seq, methylation, proteomics
- AI-driven drug discovery: AutoDock Vina, PyRx, QSAR, virtual screening, SMILES/InChI, PubChem, ChEMBL, ZINC, DrugBank, SwissADME
- CRISPR: gRNA design, off-target analysis
- Bioinformatics: BLAST, Clustal, MUSCLE, SwissModel, Phyre2; NCBI, UniProt, PDB, KEGG, cBioPortal, TCGA
- Galaxy, agentic AI and LLM-based workflows

Desirable Experience

Publications, research projects or a thesis in computational biology or AI-biology integration, and experience with large biological datasets and computational pipelines.

📌 Trainer & Scientist – AI/ML, Cancer Genomics & Computational Biology (Bengaluru)
🏢 BioTecNika
📍 Bengaluru