Labor Dispatch for Machine Learning Model Construction Tender

Notice for Labor Dispatch for Machine Learning Model Construction and Verification Work for Cancer Surgery Using Xr Navigation (2026-Wa-048) in Japan. The reference ID of the tender is 135270982 and it is closing on 21 Feb 2026.

Tender Details

Country: Japan
Summary: Labor Dispatch for Machine Learning Model Construction and Verification Work for Cancer Surgery Using Xr Navigation (2026-Wa-048)
JPT Ref No: 135270982
Deadline: 21 Feb 2026
Financier: Self Financed
Purchaser Ownership: Government
Tender Value: Refer Document
Notice Type: Tender
Document Ref. No.:
Purchaser's Detail:
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Description:
Labor dispatch for machine learning model construction and verification work for cancer surgery using XR navigation (2026-WA-048) Description: Labor dispatch for machine learning model construction and verification work oriented to cancer surgery using XR navigation (2026-WA-048) Return to the list of worker dispatch workers Procurement project name XR Navigation oriented towards cancer surgery... Deadline: 2026-02-21 [Disclaimer: This notice does not specify a specific deadline, so we have added 15 days from the date of posting]
Documents:

Tender Notice

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Labor Dispatch for Machine Learning Model Construction and Verification Work for Cancer Surgery Using Xr Navigation (2026-Wa-048) - Japan Tender

The NATIONAL RESEARCH AND DEVELOPMENT AGENCY RIKEN, a Government sector organization in Japan, has announced a new tender for Labor Dispatch for Machine Learning Model Construction and Verification Work for Cancer Surgery Using Xr Navigation (2026-Wa-048). This tender is published on JapanTenders under JPT Ref No: 135270982 and is categorized as a Tender. Interested and eligible suppliers are invited to participate by reviewing the tender documents and submitting their bids before the deadline on 2026-02-21.

The estimated tender value is Refer Document, and full details, including technical specifications and submission requirements, are provided in the official tender documents. Ensure all submissions meet the criteria outlined to be considered for evaluation.

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