Jivanu Therapeutics is an early stage, investor-backed biotechnology company focused on microbiome-based therapeutics for various diseases in Indian population.

Jivanu Therapeutics are seeking a highly skilled Computational Biologist to join our team in the analysis of large volumes of microbiome data from the gut. The ideal candidate will have a strong background in computational disciplines, with a focus on analyzing microbiome, mycobiome, and viriome data. In addition to expertise in microbiome analysis, the successful candidate will also be comfortable working with metabolomics and proteomics data.

Responsibilities:

1. Microbiome Analysis: Utilize advanced computational techniques to analyze large-scale gut microbiome data, including taxonomic profiling, diversity analysis, and functional annotation.
2. Mycobiome and Viriome Analysis: Apply computational methods to analyze fungal and viral communities within the gut microbiome, including characterization of community structure and functional potential.
3. Integration of Multi-Omics Data: Integrate microbiome data with metabolomics and proteomics data to gain comprehensive insights into host-microbiome interactions and metabolic pathways.
4. Algorithm Development: Develop novel computational algorithms and analytical pipelines for the analysis of complex microbiome datasets, with a focus on scalability and reproducibility.
5. Data Visualization: Generate clear and informative visualizations to communicate findings effectively to both technical and non-technical stakeholders.
6. Collaboration: Collaborate closely with interdisciplinary teams including biologists, bioinformaticians, and clinicians to interpret findings and drive research objectives.
7. Quality Assurance: Ensure the accuracy and reliability of computational analyses through rigorous quality control measures and validation procedures.
8. Stay Updated: Stay abreast of the latest advancements in computational biology, microbiome research, and related fields, and incorporate relevant methodologies into analyses.

Hybrid working model of working in person as well as work from home can be discussed.

Location: Bengaluru, Karnataka

• Competitive salary commensurate with experience.
• Comprehensive benefits package including health coverage.
• Opportunities for professional development and continuing education.
• Collaborative and innovative work environment at the forefront of microbiome research.
• Potential for career advancement and leadership opportunities within the organization.

M.S. or Ph.D. in a computational discipline such as Bioinformatics, Computational Biology, Computer Science, or a related field.

• Strong programming skills, particularly in languages such as Python, R, or Perl.
• Proficiency in bioinformatics tools and software packages commonly used for microbiome analysis (e.g., QIIME2, mothur, MetaPhlAn).
• Experience working with large-scale omics datasets, including microbiome, metabolomics, and proteomics data.
• Familiarity with statistical analysis methods for high-dimensional biological data.
• Excellent communication skills and ability to collaborate effectively within interdisciplinary teams.
• Demonstrated ability to independently design and execute computational analyses and develop novel algorithms.
• Strong problem-solving skills and attention to detail.

Preferred Qualifications:
1. Experience with machine learning techniques applied to biological data.
2. Knowledge of cloud computing platforms and experience with parallel computing environments.
3. Prior experience in gut microbiome research or related fields.
4. Publications in peer-reviewed journals showcasing contributions to computational biology or microbiome research.

To apply, please submit a resume/​CV and cover letter outlining your qualifications and interest in the position to hr@​jivanutx.​com . Additionally, provide examples of relevant projects or publications, along with contact information for references. They are committed to fostering diversity and inclusion within our team and encourage individuals from underrepresented backgrounds to apply.