OSDDIN Contributor Interest Form.

About OSDDIN

OSDDIN is a collaborative platform bringing together clinicians, researchers, bioinformaticians, AI/ML researchers, engineers, and students to address important health challenges in India.

We are building multidisciplinary teams across institutions and would like to understand your background, expertise, interests, and how you would like to contribute.

About you

Profile photo

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1. Name and contact details

Name, email, institution/organisation, and location.

Name *

Email *

Institution / Organisation *

Location

2. Current role *

Faculty / PIClinicianScientist / ResearcherPostdoctoral ResearcherPhD StudentMaster’s StudentUndergraduate StudentEngineer / Industry ProfessionalOther:

3. Field and current work *

Briefly describe your research, clinical, or technical background and what you currently work on.

Expertise and interests

4. Relevant expertise *

Select all that apply.

Clinical researchBiology / Life SciencesGenomics / TranscriptomicsSingle-cell / Multi-omicsBioinformaticsData ScienceAI / Machine LearningSoftware EngineeringKnowledge GraphsStatistics / EpidemiologyPublic HealthJavaScriptTypeScriptNeo4jClickHouseNext.jsNestJSDockerRedisOther:

5. What health or research areas are you most interested in contributing to? *

6. Do you have a specific problem, project, dataset, or research question that you would like to bring to OSDDIN?

Optional.

How would you like to contribute?

7. How would you like to participate? *

Select all that apply.

Lead or co-lead a projectContribute hands-on to a projectProvide clinical or scientific expertiseMentor students or junior contributorsDevelop datasets, analyses, pipelines, or softwareSupport OSDDIN coordination and community activitiesOpen to discussing where I could contribute

8. What level of time commitment would be realistic for you?

For example: 1–5 hours per week, 5–10 hours per week, 10+ hours per week, or a few focused weeks per quarter.

9. What would help you contribute effectively?

For example, access to collaborators, datasets, computational resources, mentorship, or training.

10. Relevant links

Publications, Google Scholar, ORCID, GitHub, LinkedIn, personal website, or other relevant work.