# EURAXESS Jobs Scraper (`jobsapi/euroaxess-jobs-search-scraper`) Actor

Read public EURAXESS research job cards and detail pages for job, organisation, research, deadline, description, salary text, contract, and work-location fields. Contact data is omitted and access failures fail closed.

- **URL**: https://apify.com/jobsapi/euroaxess-jobs-search-scraper.md
- **Developed by:** [Jobs API](https://apify.com/jobsapi) (community)
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $2.99 / 1,000 euraxess research positions

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## EURAXESS Jobs Search Scraper

This Apify Actor reads the public [EURAXESS](https://euraxess.ec.europa.eu) search results and emits source-backed research-job records from visible result cards. A historical observation (2026-09-22) found public `/jobs/{id}` links redirecting to `/jobs/search` on the ordinary direct route; current source access was not checked during the offline lifecycle audit. The Actor therefore retains those URLs as unverified detail links and does not claim detail-page fields that it could not fetch.

### Public input

```json
{
  "query": "biology",
  "maxPages": 1,
  "maxItems": 3
}
```

The Actor uses ordinary direct HTTPS requests, sequential pagination, and no proxy, stealth, fingerprint, identity, retry, fixture, or temporary context controls.

### Source fields

The existing parser handles job ID, title, offer type, country, organisation and profile URL, posted date, summary, department, work-location summary, research fields, researcher profile, funding programme, and application deadline when those values are present on an accessible card. This offline audit did not verify the current source fields. Records preserve parsed fields, normalized dates, arrays for visible labels, listing/detail URL provenance, request headers/status, source evidence, and quality counts.

`detailEnriched` and `detailAvailable` are explicitly `false` for the current run shape. This is intentional: a live Chrome click and an ordinary direct request to a public detail URL both returned to the search route, so no detail-only value is fabricated.

### Access policy

HTTP 401/403/429/451 or a visible source-authored verification/access-denial challenge stops further requests and discards unpersisted staged jobs. The outcome is `SUCCEEDED/SKIPPED` if no eligible rows were stored, or `SUCCEEDED/LIMITED` if a stored prefix already exists. HTTP 407, redirects, unverified HTTP responses, response-read failures, transport failures, parser uncertainty, and zero-qualified-record quality outcomes are `SUCCEEDED/DEFERRED`; they are not treated as proof that EURAXESS blocked access. `NO_DATA` requires visible first-party empty-result evidence for every requested search. Fatal runtime or storage failures before any eligible row is stored are `FAILED/FAILED`; after a stored prefix they are `SUCCEEDED/LIMITED`. Diagnostics and request receipts are stored only in the key-value store, never in the jobs dataset. The Actor never switches proxies, identities, browser fingerprints, or alternate routes to work around a restriction.

The platform run status is always `SUCCEEDED` or `FAILED`; `resultStatus` separately describes `COMPLETE`, `LIMITED`, `SKIPPED`, `DEFERRED`, `NO_DATA`, or `FAILED`. Only successfully awaited `pushData` calls count as stored rows. A zero-row fatal runtime/storage failure calls `Actor.fail()` and reports `FAILED/FAILED`; eligible rows stored before a later failure are retained and reported as `SUCCEEDED/LIMITED`.

### Output and validation

The strict dataset schema is `.actor/dataset_schema.json`; dataset rows are complete, source-backed job cards only. The Actor also stores `OUTPUT_SUMMARY`, `REQUEST_RECEIPTS`, `RUN_DIAGNOSTICS`, and `OUTPUT` in the default key-value store. `OUTPUT_SUMMARY` and `OUTPUT` expose separate platform and result statuses plus reconciled staged/stored counts.

```text
npm install
npm test
apify validate-schema
apify run --purge --input-file ./INPUT.json
npm run validate:dataset -- storage
```

The validator requires actor-generated source-card records with successful direct listing receipts, honest listing/detail provenance, and more than 20 meaningful populated fields per record.

# Actor input Schema

## `query` (type: `string`):

Public EURAXESS keyword search, such as biology, engineering, or postdoctoral.

## `maxPages` (type: `integer`):

Maximum public result pages to inspect sequentially.

## `maxItems` (type: `integer`):

Maximum distinct public job-card records to emit.

## Actor input object example

```json
{
  "query": "biology",
  "maxPages": 1,
  "maxItems": 3
}
```

# Actor output Schema

## `dataset` (type: `string`):

No description

## `runSummary` (type: `string`):

No description

## `requestReceipts` (type: `string`):

No description

## `diagnostics` (type: `string`):

No description

## `output` (type: `string`):

No description

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {};

// Run the Actor and wait for it to finish
const run = await client.actor("jobsapi/euroaxess-jobs-search-scraper").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {}

# Run the Actor and wait for it to finish
run = client.actor("jobsapi/euroaxess-jobs-search-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{}' |
apify call jobsapi/euroaxess-jobs-search-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,jobsapi/euroaxess-jobs-search-scraper"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/NbTkiw8lferf47BmM/builds/csdnUiGibSa2gG1f2/openapi.json