# Universitat de Barcelona PhD Vacancy Scraper (`nomad-agent/ub-doctoral-scraper`) Actor Extract doctoral-programme vacancies and PhD calls from Universitat de Barcelona. An AI step (bring your own Anthropic key) parses the university's pages into clean records: title, programme, deadline, apply URL. Best for PhD-alert services covering Spain and Catalonia. - **URL**: https://apify.com/nomad-agent/ub-doctoral-scraper.md - **Developed by:** [Nomad.Dev](https://apify.com/nomad-agent) (community) - **Categories:** Jobs - **Stats:** 2 total users, 0 monthly users, 75.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. 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. Actors are written with capital "A". ## 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. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Universitat de Barcelona PhD Vacancy Scraper Fetch PhD and doctoral-programme calls from Universitat de Barcelona, parsed into clean records by an AI extraction step (BYO Anthropic or Mistral key). > **Bring your own key.** This Actor uses either Claude (Anthropic) or Mistral for AI extraction — pick with `provider`. Pass `anthropicApiKey` (provider `"anthropic"`, default) or `mistralApiKey` (provider `"mistral"`) in the input (or set `ANTHROPIC_API_KEY`/`MISTRAL_API_KEY` in the run's environment). Without a matching key the run fails immediately with a clear error message; it never silently succeeds with 0 items. ### AI provider: Anthropic vs Mistral `provider` selects which AI does discovery + extraction: - **`anthropic`** (default) — a Claude agent uses Anthropic's built-in web-search and web-fetch tools to browse UB's pages and follow one promising link. - **`mistral`** — UB's pages carry no bot protection, so this path fetches them directly with plain HTTP (no search-engine detour needed), follows a few links whose anchor text/URL look vacancy-related (`vacanc`, `phd`, `doctoral`, `predoctoral`, `convocat`, `beca`, etc.), then ONE Mistral call extracts structured postings from the combined fetched text. Output shape and the no-guessing extraction rules (never fabricate `deadline`, only include genuine open vacancies) are identical either way. ### What Universitat de Barcelona PhD data does this scraper extract? Each result is one flat JSON record per job posting: | Field | Meaning | |---|---| | `id` | Stable source-side identifier (the posting URL where available) | | `title` | Job title / thesis topic as posted | | `company` | Always `"Universitat de Barcelona"` | | `location` | Always `"Barcelona, Spain"` | | `url` | Direct link to the posting | | `postedAt` | Posting date where the source states it, else `null` | | `deadline` | Application/thesis deadline where the source states it, else `null` | | `snippet` | Short description excerpt | | `source` | Always `"ub_doctoral"` | ### How to scrape Universitat de Barcelona PhD with this Actor 1. Click **Try for free** / **Run** — no login to the target site, no cookies, no proxies to configure. 2. Adjust the input (`postedSince`, `maxItems`) or keep the defaults — just remember to supply your own `anthropicApiKey`. 3. Run it and export the dataset as JSON, CSV or Excel, or read it over the [API](https://docs.apify.com/api/v2). Run it from your own code: ```python from apify_client import ApifyClient client = ApifyClient("") run = client.actor("nomad-agent/ub-doctoral-scraper").call(run_input={"maxItems": 50}) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item["title"], "—", item["company"], item["url"]) ```` Or a single HTTP call that runs the Actor and returns items in one response: ```bash curl -X POST \ "https://api.apify.com/v2/acts/nomad-agent~ub-doctoral-scraper/run-sync-get-dataset-items?token=" \ -H "Content-Type: application/json" \ -d '{"maxItems": 50}' ``` ### Input | Field | Type | Default | Notes | |---|---|---|---| | `provider` | string | `"anthropic"` | Which AI provider runs discovery + extraction: `"anthropic"` (Claude + built-in web search/fetch) or `"mistral"` (direct page fetch + Mistral extraction). | | `anthropicApiKey` | string | — | Required when `provider` is `"anthropic"`. Your Anthropic API key (sk-ant-...). Can also be set via the `ANTHROPIC_API_KEY` environment variable. Anthropic bills usage on this key to your own Anthropic account, separately from Apify's charges below. | | `mistralApiKey` | string | — | Required when `provider` is `"mistral"`. Your Mistral API key. Can also be set via the `MISTRAL_API_KEY` environment variable. Mistral bills usage on this key to your own Mistral account, separately from Apify's charges below. | | `mistralModel` | string | `"mistral-small-latest"` | Mistral model for extraction (provider `"mistral"` only): `mistral-small-latest` (default — matches larger models on this small, well-scoped task), `mistral-medium-latest`, or `mistral-large-latest`. | | `maxItems` | integer | `12` | Maximum number of PhD vacancies to return (0 = no limit, capped internally at 50 for cost safety). Each returned vacancy is billed as one Apify result, and every run also consumes AI-provider tokens billed to your own key. | | `postedSince` | string (date) | — | Only return vacancies posted on or after this date. Vacancies whose posted date can't be read are still included, not silently dropped. Leave empty to disable the filter. | | `model` | string | `"claude-haiku-4-5-20251001"` | *(Advanced)* Claude model to use for scraping. A fast, low-cost model is recommended. | ### Output example ```json { "id": "https://web.ub.edu/en/doctoral-vacancies/physics-complex-systems", "title": "PhD Position — Complex Systems, Department of Physics", "company": "Universitat de Barcelona", "location": "Barcelona, Spain", "url": "https://web.ub.edu/en/doctoral-vacancies/physics-complex-systems", "postedAt": "2026-06-18", "deadline": "2026-07-31", "snippet": "The doctoral programme in Physics invites applications for a funded predoctoral contract on complex systems modelling...", "source": "ub_doctoral" } ``` `postedAt` and `deadline` are `null` when the source page doesn't state them — never an empty string. ### Pricing Pay per event: **$0.05 per Actor start** and **$0.004 per job returned**. 100 jobs ≈ $0.45. No subscription, no rental — you pay only for what you fetch. **Bring-your-own-key cost:** this Actor calls the AI provider you pick (`provider`) using your own `anthropicApiKey` or `mistralApiKey`. That provider bills usage (web search/page fetches + model tokens) directly to your own account — separately from, and in addition to, the Apify charges above. Apify has no visibility into or control over that cost; check [Anthropic's](https://www.anthropic.com/pricing) or [Mistral's](https://mistral.ai/pricing) own pricing for the model you select. ### Integrations Export results as JSON, CSV or Excel from the dataset; call this Actor from Make, Zapier or n8n; run it programmatically with `run-sync-get-dataset-items`; or use it from AI agents through the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp). ### Use cases - PhD-alert bots for Spain/Catalonia - Academic aggregation boards - Doctoral-programme deadline tracking - Research-career consulting ### FAQ **Is it legal to scrape Universitat de Barcelona PhD?** This Actor reads only publicly available job postings — data any visitor can see without logging in. No personal data behind authentication is touched. Review the target site's terms and your local regulations for your specific use case. **Do I need an account on the target site?** No. Postings are fetched from public pages/APIs — no login, cookies or session tokens. **How fresh is the data?** Every run fetches live listings directly from UB's pages via Claude's web search — there is no caching, so each run reflects what's on the site right now. **How many jobs can I get?** `maxItems` caps the run (0 = no explicit limit, internally capped at 50 for cost safety). This is a single-institution source, so most runs return well under that. **Something broken or missing?** Open an issue on the Actor's **Issues** tab — it is monitored and reliability fixes ship fast. ### Related Actors - [Research & Academic Jobs Scraper — 10 Sources](https://apify.com/nomad-agent/researcher-bundle) - [Ikerbasque Jobs Scraper — Basque Research Roles](https://apify.com/nomad-agent/ikerbasque-scraper) - [EURAXESS Jobs Scraper — EU Research Positions](https://apify.com/nomad-agent/euraxess-scraper) # Actor input Schema ## `provider` (type: `string`): Which AI provider runs discovery + extraction. "anthropic" (default) uses a Claude agent with Anthropic's built-in web-search and web-fetch tools. "mistral" fetches UB's landing/HR pages directly (plain HTTP, no bot protection on this source) and follows a few vacancy-looking links, then a Mistral model extracts structured fields from the combined page text -- pick this if you'd rather bring a Mistral key than an Anthropic one. ## `anthropicApiKey` (type: `string`): Your Anthropic API key (sk-ant-...). Required when provider is "anthropic" — this Actor uses Claude with web search to find and parse UB vacancy pages. Can also be set via the ANTHROPIC\_API\_KEY environment variable. Anthropic bills usage on this key to your own Anthropic account, separately from Apify's charges for this Actor. ## `mistralApiKey` (type: `string`): Your Mistral API key. Required when provider is "mistral". Can also be set via the MISTRAL\_API\_KEY environment variable. Mistral bills usage on this key to your own Mistral account, separately from Apify's charges for this Actor. ## `mistralModel` (type: `string`): Mistral model for extraction (provider="mistral" only). Small is the default -- testing found it matches larger Mistral models on this task (extraction is small and well-scoped) at a fraction of the cost. ## `maxItems` (type: `integer`): Maximum number of PhD vacancies to return (0 = no limit, capped internally at 50 for cost safety). Each returned vacancy is billed as one Apify result, and every run also consumes Anthropic tokens billed separately to your own API key. ## `postedSince` (type: `string`): Only return vacancies posted on or after this date. Vacancies whose posted date can't be read are still included, not silently dropped. Leave empty to disable the filter. ## `model` (type: `string`): Claude model to use for scraping. A fast, low-cost model is recommended. ## Actor input object example ```json { "provider": "anthropic", "mistralModel": "mistral-small-latest", "maxItems": 12, "model": "claude-haiku-4-5-20251001" } ``` # 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 '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("nomad-agent/ub-doctoral-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 '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = {} # Run the Actor and wait for it to finish run = client.actor("nomad-agent/ub-doctoral-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).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 nomad-agent/ub-doctoral-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=nomad-agent/ub-doctoral-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Universitat de Barcelona PhD Vacancy Scraper", "description": "Extract doctoral-programme vacancies and PhD calls from Universitat de Barcelona. An AI step (bring your own Anthropic key) parses the university's pages into clean records: title, programme, deadline, apply URL. Best for PhD-alert services covering Spain and Catalonia.", "version": "0.1", "x-build-id": "0LSSgUidhQhsVOUcp" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/nomad-agent~ub-doctoral-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-nomad-agent-ub-doctoral-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/nomad-agent~ub-doctoral-scraper/runs": { "post": { "operationId": "runs-sync-nomad-agent-ub-doctoral-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/nomad-agent~ub-doctoral-scraper/run-sync": { "post": { "operationId": "run-sync-nomad-agent-ub-doctoral-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "provider": { "title": "AI provider", "enum": [ "anthropic", "mistral" ], "type": "string", "description": "Which AI provider runs discovery + extraction. \"anthropic\" (default) uses a Claude agent with Anthropic's built-in web-search and web-fetch tools. \"mistral\" fetches UB's landing/HR pages directly (plain HTTP, no bot protection on this source) and follows a few vacancy-looking links, then a Mistral model extracts structured fields from the combined page text -- pick this if you'd rather bring a Mistral key than an Anthropic one.", "default": "anthropic" }, "anthropicApiKey": { "title": "Anthropic API key", "type": "string", "description": "Your Anthropic API key (sk-ant-...). Required when provider is \"anthropic\" — this Actor uses Claude with web search to find and parse UB vacancy pages. Can also be set via the ANTHROPIC_API_KEY environment variable. Anthropic bills usage on this key to your own Anthropic account, separately from Apify's charges for this Actor." }, "mistralApiKey": { "title": "Mistral API key", "type": "string", "description": "Your Mistral API key. Required when provider is \"mistral\". Can also be set via the MISTRAL_API_KEY environment variable. Mistral bills usage on this key to your own Mistral account, separately from Apify's charges for this Actor." }, "mistralModel": { "title": "Mistral model", "enum": [ "mistral-small-latest", "mistral-medium-latest", "mistral-large-latest" ], "type": "string", "description": "Mistral model for extraction (provider=\"mistral\" only). Small is the default -- testing found it matches larger Mistral models on this task (extraction is small and well-scoped) at a fraction of the cost.", "default": "mistral-small-latest" }, "maxItems": { "title": "Max items", "minimum": 0, "maximum": 50, "type": "integer", "description": "Maximum number of PhD vacancies to return (0 = no limit, capped internally at 50 for cost safety). Each returned vacancy is billed as one Apify result, and every run also consumes Anthropic tokens billed separately to your own API key.", "default": 12 }, "postedSince": { "title": "Posted since", "type": "string", "description": "Only return vacancies posted on or after this date. Vacancies whose posted date can't be read are still included, not silently dropped. Leave empty to disable the filter." }, "model": { "title": "Anthropic model", "type": "string", "description": "Claude model to use for scraping. A fast, low-cost model is recommended.", "default": "claude-haiku-4-5-20251001" } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```