# jobs.ac.uk Scraper — UK Academic & Research Jobs (`nomad-jobs/jobs-ac-uk-scraper`) Actor Extract live academic vacancies from jobs.ac.uk, the UK's main academic job board: lectureships, postdocs, fellowships, research and professional-services roles. Each record carries title, university, location, salary, closing date and apply URL. - **URL**: https://apify.com/nomad-jobs/jobs-ac-uk-scraper.md - **Developed by:** [Nomad.Dev](https://apify.com/nomad-jobs) (community) - **Categories:** Jobs - **Stats:** 3 total users, 1 monthly users, 100.0% 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 ## jobs.ac.uk Scraper — UK Academic & Research Jobs Scrape current academic and research vacancies from jobs.ac.uk — the UK and Europe's leading academic job board. ### What jobs.ac.uk data does this scraper extract? Each result is one flat JSON record per job posting: | Field | Meaning | |---|---| | `jobId` | Stable source-side job identifier, parsed from the posting URL (e.g. `DSC994`) | | `id` | Alias of `jobId` — same value, kept for field-name consistency across our Actors | | `title` | Job title as posted | | `company` | Hiring institution / organisation, or `null` if the listing omits it | | `location` | Location / duty station; defaults to `"United Kingdom"` when the listing shows no city | | `salary` | Salary text as displayed on the listing, or `""` when no salary is shown | | `postedAt` | ISO 8601 date (`YYYY-MM-DD`) the listing was placed, or `null` if it can't be parsed | | `deadline` | ISO 8601 date (`YYYY-MM-DD`) parsed from the listing's "Closes"/"Expires" chip, the raw text when it can't be parsed, or `null` when the listing shows no closing date | | `url` | Direct link to the posting | ### How to scrape jobs.ac.uk 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 (keyword, filters, `maxItems`) or keep the defaults. 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-jobs/jobs-ac-uk-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-jobs~jobs-ac-uk-scraper/run-sync-get-dataset-items?token=" \ -H "Content-Type: application/json" \ -d '{"maxItems": 50}' ``` ### Input | Field | Type | Default | Notes | |---|---|---|---| | `keywords` | array | *(built-in defaults)* | List of keyword queries to fan across. Each keyword is searched separately and results are merged (deduped by URL). Leave empty to use the built-in research-oriented defaults: social science, politics, psychology, humanities, international development, research. | | `maxItems` | integer | `25` | Maximum number of job postings to return across all keyword queries (max `1000`). Each job returned is billed as one result event — see Pricing. Set to 0 for no limit. | | `pageSize` | integer | `25` | How many results to request per keyword search (portal maximum is 25). Increase if you are running with a large `maxItems` and few keywords. | | `postedSince` | integer | `0` | Only keep postings placed within this many days (max `365`). Applied locally after fetching — jobs.ac.uk has no server-side date filter. Listings whose date can't be read are always kept. Set 0 to disable. | | `cacheTtlSeconds` | integer | `1800` | *(Advanced)* How long to reuse a previous fetch instead of contacting jobs.ac.uk again, in seconds. Set to 0 to always fetch fresh data. | ### Output example ```json { "jobId": "DSC994", "id": "DSC994", "title": "Admissions & Student Recruitment Coordinator", "company": "University of Strathclyde", "location": "Glasgow", "salary": "£28,031 to £30,378 per annum", "postedAt": "2026-07-02", "deadline": "2026-07-08", "url": "https://www.jobs.ac.uk/job/DSC994/admissions-and-student-recruitment-coordinator-828134" } ``` ### Integrations Export the dataset as JSON, CSV or Excel from the Console, pull it over the [Apify API](https://docs.apify.com/api/v2) (including `run-sync-get-dataset-items` for a single blocking call), wire it into Make/Zapier/n8n, or drive it from an AI agent via the [Apify MCP server](https://apify.com/apify/actors-mcp-server). ### 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. ### Use cases - Academic job boards and PhD/postdoc alert bots - University HR benchmarking - Research-funding and hiring-trend analysis - Career services for early-career researchers ### FAQ **Is it legal to scrape jobs.ac.uk?** 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. Results are cached for `cacheTtlSeconds` (default 30 min, set 0 to always hit the source live). **How many jobs can I get?** `maxItems` caps the run (set 0 where supported for no cap). Most sources paginate from newest to oldest. **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-jobs/researcher-bundle) - [EURAXESS Jobs Scraper — EU Research Positions](https://apify.com/nomad-jobs/euraxess-scraper) - [University of Copenhagen PhD Jobs Scraper (KU)](https://apify.com/nomad-jobs/math-ku-phd-scraper) - [Universitat de Barcelona PhD Vacancy Scraper](https://apify.com/nomad-jobs/ub-doctoral-scraper) # Actor input Schema ## `keywords` (type: `array`): List of keyword queries to fan across. Each keyword is searched separately and results are merged (deduped by URL). Leave empty to use the built-in research-oriented defaults: social science, politics, psychology, humanities, international development, research. ## `maxItems` (type: `integer`): Maximum number of job postings to return across all keyword queries. Each job returned is billed as one result event — see the Pricing tab. Set to 0 for no limit. ## `pageSize` (type: `integer`): How many results to request per keyword search (portal maximum is 25). Increase if you are running with a large maxItems and few keywords. ## `postedSince` (type: `integer`): Only keep postings placed within this many days. Applied locally after fetching, since jobs.ac.uk has no server-side date filter — postedAt is parsed from each listing's "Date Placed" text and compared here. Listings whose date can't be read are always kept, not silently dropped. Set 0 (default) to disable and return all fetched listings regardless of age. ## `cacheTtlSeconds` (type: `integer`): How long to reuse a previous fetch instead of contacting jobs.ac.uk again, in seconds. Speeds up repeated runs that use the same keywords. Set to 0 to always fetch fresh data. ## Actor input object example ```json { "keywords": [ "social science", "psychology", "bioinformatics" ], "maxItems": 25, "pageSize": 25, "postedSince": 0, "cacheTtlSeconds": 1800 } ``` # 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-jobs/jobs-ac-uk-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-jobs/jobs-ac-uk-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-jobs/jobs-ac-uk-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=nomad-jobs/jobs-ac-uk-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "jobs.ac.uk Scraper — UK Academic & Research Jobs", "description": "Extract live academic vacancies from jobs.ac.uk, the UK's main academic job board: lectureships, postdocs, fellowships, research and professional-services roles. Each record carries title, university, location, salary, closing date and apply URL.", "version": "0.1", "x-build-id": "gchiBgURfDnTkiuql" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/nomad-jobs~jobs-ac-uk-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-nomad-jobs-jobs-ac-uk-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/nomad-jobs~jobs-ac-uk-scraper/runs": { "post": { "operationId": "runs-sync-nomad-jobs-jobs-ac-uk-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/nomad-jobs~jobs-ac-uk-scraper/run-sync": { "post": { "operationId": "run-sync-nomad-jobs-jobs-ac-uk-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "keywords": { "title": "Keywords", "type": "array", "description": "List of keyword queries to fan across. Each keyword is searched separately and results are merged (deduped by URL). Leave empty to use the built-in research-oriented defaults: social science, politics, psychology, humanities, international development, research.", "items": { "type": "string" } }, "maxItems": { "title": "Max items", "minimum": 0, "maximum": 1000, "type": "integer", "description": "Maximum number of job postings to return across all keyword queries. Each job returned is billed as one result event — see the Pricing tab. Set to 0 for no limit.", "default": 25 }, "pageSize": { "title": "Results per keyword query", "minimum": 1, "maximum": 25, "type": "integer", "description": "How many results to request per keyword search (portal maximum is 25). Increase if you are running with a large maxItems and few keywords.", "default": 25 }, "postedSince": { "title": "Posted within last N days", "minimum": 0, "maximum": 365, "type": "integer", "description": "Only keep postings placed within this many days. Applied locally after fetching, since jobs.ac.uk has no server-side date filter — postedAt is parsed from each listing's \"Date Placed\" text and compared here. Listings whose date can't be read are always kept, not silently dropped. Set 0 (default) to disable and return all fetched listings regardless of age.", "default": 0 }, "cacheTtlSeconds": { "title": "Cache TTL (seconds)", "minimum": 0, "type": "integer", "description": "How long to reuse a previous fetch instead of contacting jobs.ac.uk again, in seconds. Speeds up repeated runs that use the same keywords. Set to 0 to always fetch fresh data.", "default": 1800 } } }, "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 } } } } } } } } } } ```