Internshala
From Internshala's careers page
Status: listed on the employer's own careers page when we last checked (daily). Confirm on their site before applying.
Key responsibilities:
1. Perform WGS, WES, NGS, and RNA-seq data analysis, including quality control, alignment, variant calling, annotation, and interpretation.
2. Develop, customise, optimise, test, and validate bioinformatics pipelines.
3. Apply AI/ML and deep learning techniques to genomic, transcriptomic, proteomic, and clinical datasets.
4. Develop predictive models for cancer classification, biomarker discovery, molecular subtype identification, and treatment-response prediction.
5. Perform multi-omics integration, differential gene expression, pathway analysis, and biomarker identification.
6. Work on cancer research projects involving colorectal, prostate, peritoneal, and lung cancers.
7. Support computational biology and de novo drug discovery research.
8. Conduct research and develop methodologies for ageing-related studies and treatment-response prediction.
9. Integrate bioinformatics and AI/ML workflows into the BILD AI platform in coordination with software and research teams.
10. Support R&D projects, including therapeutic research and other biomedical applications.
11. Prepare research reports, scientific manuscripts, publications, and technical documentation.
12. Coordinate with research collaborators and manage assigned project deliverables.
have minimum 1 years of experience
₹ 3,00,000 - 4,00,000 /year
1 year(s)
2026-12-06 23:59:59
scikit-learn, TensorFlow and PyTorch
1. Degree in Bioinformatics, Computational Biology, Genomics, Biotechnology, Computer Science, Data Science, Biomedical Engineering, or a related field (BTech/MTech/MSc/MS).
2. Knowledge of bioinformatics techniques, including NGS, WGS, WES, RNA-seq, variant calling, annotation, and genomic data analysis.
3. Familiarity with bioinformatics tools such as BWA, GATK, SAMtools, BCFtools, VEP, Mutect2, FastQC, and MultiQC.
4. Strong proficiency in Python and/or R, with familiarity with Linux/Unix.
5. Knowledge of machine learning, deep learning, predictive modelling, classification, regression, and model evaluation.
6. Familiarity with Scikit-learn, TensorFlow, and/or PyTorch.
7. Experience in multi-omics integration, differential gene expression, statistical analysis, and biomarker discovery.
8. Familiarity with genomic databases such as TCGA, GEO, NCBI, Ensembl, ClinVar, and COSMIC.
9. Experience in cancer genomics and treatment-response research.
10. Exposure to single-cell RNA sequencing and spatial transcriptomics.
11. Knowledge of computational drug discovery.
12. Experience with cloud-based computational environments.
13. Candidates with combined expertise in bioinformatics, programming, and AI/ML are preferred.
14. Research publications will be an advantage.
Biodesign Innovation Labs is a start-up focused on delivering high-quality, affordable, simple-to-use portable respiratory assist, intensive care, critical care, and other respiratory and emergency care life-saving innovations.
Scores your resume against this job the way resume scanners do: the job's hard and soft skills, searchability, recruiter tips and formatting.
Create a free account to see your score. Your resume stays in this browser until then, and we never store it.
Already a member? Sign in