MEDGENOME | Senior Machine Learning and AI Scientist | delhi

2 weeks ago

delhi, India MEDGENOME Full time

Find your next role with MedGenome Labs Ltd. We are the market leader in clinical genomic space in India and offers a comprehensive rangeof diagnostic servicesto doctors and researchers. We operate the largest CAP accredited Next Generation Sequencing (NGS) lab in Southeast Asia housing cutting-edge genome sequencing platforms. MedGenome is the founding member of GenomeAsia 100K, an initiative to sequence 100,000 Genomes in Asia.

We have an exciting opportunity for the position of Senior Machine Learning and AI Scientist in Bengaluru location. It is a full time and work from office opportunity.

Roles and Responsibilities:

Lead the development of AI/ML models for analysis of large-scale multi-omics dataset including genomics, transcriptomics, proteomics, and metabolomics, to uncover new biological insights and biomarkers.
Build machine learning model from clinical and research diagnostics data (genomics data, phenotype, clinical notes, histology, literatures and others) to prioritize disease causing variants/mutations.
Lead the development of AI/ML to data mine omics data, including genomics, transcriptomics, proteomics, and metabolomics, to uncover new biological insights and biomarkers.
Collaborate with biologists, bioinformaticians, genome analysts, software engineering and data scientists to design and implement cutting-edge computational methods for integrating multi-omics data sets.
Implement advanced machine learning techniques such as deep learning, reinforcement learning, and unsupervised learning for complex biological data, with a focus on improving predictions and classifications in disease and discovery research.
Implement machine learning and AI solutions that boost the efficiency and effectiveness of clinical diagnostics
Utilize LLMs to extract meaningful insights from genetic data, including genetic variations, gene expression patterns, and regulatory networks associated with phenotypic traits or diseases.
Collaborate with interdisciplinary teams to design and execute research projects, leveraging ML/AI approaches, and contribute to data interpretation and result validation.
Publish scientific findings in peer-reviewed journals and present research at conferences, establishing thought leadership in the field.

Skills and Experience:

6+ years of experience in Machine Learning & AI in the space of Genomics or Biotechnology.
Experience working in an industry setting with machine learning applications in computational biology or omics.
Expertise in building and deploying machine learning models, particularly in areas such as genomics, proteomics, or multi-omics data integration.
Proficiency in programming languages such as Python and R, with experience in machine learning libraries (e.g., TensorFlow, PyTorch, Scikit-learn) and data analysis tools (e.g., Pandas, NumPy).
Strong understanding of omics data generation techniques, including NGS (next-generation sequencing) and array of exome/genome sequencing, Methylation, RNA-seq, proteomics, and other high-throughput assays.
Familiarity with bioinformatics tools, data pipelines, and databases (e.g., Nextflow, Snakemake, Ensembl, UCSC Genome Browser).
Proven track record of publishing in high-impact journals and contributing to the advancement of AI and computational biology.
Strong problem-solving skills, attention to detail, and the ability to work independently and in interdisciplinary teams.
Excellent communication and presentation skills, with the ability to explain complex AI methods to both technical and non-technical audiences.
Experience working with large biological datasets, cloud computing environments (e.g., AWS, GCP), and high-performance computing (HPC) will be a big plus.

Educational Qualification:

PhD in Computer Science, Machine Learning, Artificial Intelligence, Bioinformatics, Statistics or a related field.

If you are interested in this position, please click the APPLY NOW button for immediate employment consideration. We regret that due to volume of response, we can only contact initial successful applicants. If you have not heard from us within 7 days, then your application has been unsuccessful.

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