The NanoScrape Jobs Ac Scraper is an Apify actor that extracts job listings from jobs.ac.uk. It returns 46 fields per result including title, location, description, company_about, company_phone, priced at $5/1k company, with no API key or monthly subscription required.
Jobs.ac.uk (Academic, UK): UK academic and research jobs (source platform). GBP salary grade band, academic rank, research field, funding source, and PhD studentships.
| Field | Type | Example | Group | Fill % |
|---|---|---|---|---|
_type | string | job | Core | 100% |
id | string | 1091736 | Core | 100% |
title | string | Associate Lecturer in Geographic Data Science | Core | 100% |
employer_name | string | null | Birkbeck, University of London | Core | 100% |
employer_logo_url | string | null | https://www.jobs.ac.uk/images/employer-logos/medium/1.gif | Core | 95% |
job_url | string | https://www.jobs.ac.uk/job/DTJ141/associate-lecturer-in-geographic-data-science | Core | 100% |
application_url | string | null | https://www.jobs.ac.uk/job/DTJ141/associate-lecturer-in-geographic-data-science | Core | 100% |
source_platform | string | jobs.ac.uk | Core | 100% |
supervisor_name | string | null | (populated when data available) | Core | — |
company_about | string | null | (populated when data available) | Company | — |
company_phone | string | null | (populated when data available) | Company | — |
company_email | string | null | (populated when data available) | Company | — |
company_website | string | null | http://www.bbk.ac.uk | Company | 90% |
company_address_street | string | null | (populated when data available) | Company | — |
company_address_city | string | null | London | Company | 95% |
company_address_postcode | string | null | (populated when data available) | Company | — |
company_address_country | string | null | United Kingdom | Company | 95% |
company_active_jobs_count | integer | null | 0 | Company | 45% |
company_active_jobs | array | null | (populated when data available) | Company | 40% |
location | string | London, England | Location | 100% |
country | string | GB | Location | 100% |
description | string | null | Birkbeck, University of London, has an opportunity for an Associate Lecturer to join th... | Description | 95% |
description_full | string | null | Birkbeck, University of London, has an opportunity for an Associate Lecturer to join th... | Description | 95% |
description_html | string | null | <p>Birkbeck, University of London, has an opportunity for an Associate Le... | Description | 95% |
description_md | string | null | Birkbeck, University of London, has an opportunity for an Associate Lecturer to join th... | Description | 95% |
salary_min | number | null | 71.07 | Salary | 100% |
salary_max | number | null | 71.07 | Salary | 100% |
salary_currency | string | null | GBP | Salary | 100% |
salary_period | string | null | hour | Salary | 100% |
salary_text | string | null | £71.07 per hour. See advert text for details. | Salary | 100% |
employment_type | string | null | part-time | Employment | 95% |
contract_type | string | null | fixed-term | Employment | 95% |
duration_months | integer | null | (populated when data available) | Employment | — |
hours_per_week | number | null | (populated when data available) | Employment | — |
duration_years | number | null | (populated when data available) | Employment | — |
department | string | null | School of Social Sciences | Metadata | 80% |
posted_at | string | null | 2026-10-22 | Metadata | 100% |
scraped_at | string | 2026-10-22T08:47:29Z | Metadata | 100% |
closing_at | string | null | 2026-11-01 | Other | 100% |
position_type | string | null | academic | Other | 85% |
academic_rank | string | null | Lecturer | Other | 55% |
research_field | string | null | Data Science | Other | 50% |
funding_source | string | null | (populated when data available) | Other | 5% |
stipend_amount_gbp | number | null | (populated when data available) | Other | — |
search_query | string | null | lecturer | Other | 100% |
detail_status | string | null | ok | Other | 100% |
{
"searchQueries": [
"lecturer in computer science",
"postdoc chemistry",
"PhD studentship physics"
],
"location": "London",
"maxResults": 30,
"maxResultsPerQuery": 10,
"mode": "fast",
"maxConcurrency": 3,
"includeJobDetails": true,
"includeCompanyDetails": true
}{
"location": "London",
"maxResults": 50,
"maxResultsPerQuery": 5,
"mode": "fast",
"maxConcurrency": 3,
"includeJobDetails": true,
"includeCompanyDetails": true,
"searchUrls": [
"https://www.jobs.ac.uk/search/?keywords=lecturer+computer+science&location=London"
]
}{
"_type": "job",
"id": "1091736",
"title": "Associate Lecturer in Geographic Data Science",
"employer_name": "Birkbeck, University of London",
"company_name": "Birkbeck, University of London",
"department": "School of Social Sciences",
"employer_logo_url": "https://www.jobs.ac.uk/images/employer-logos/medium/1.gif",
"location": "London, England",
"country": "GB",
"employment_type": "part-time",
"contract_type": "fixed-term",
"duration_months": null,
"hours_per_week": null,
"salary_min": 71.07,
"salary_max": 71.07,
"salary_currency": "GBP",
"salary_period": "hour",
"salary_text": "£71.07 per hour. See advert text for details.",
"description": "Birkbeck, University of London, has an opportunity for an Associate Lecturer to join the teaching team and support the School of Social Sciences this coming Spring 2027. We are seeking an Associate Lecturer to teach on the following module: Understanding Environment Using GIS and Remote Sensing (30 hours) Thursdays, 14 January to 25 March 2027. You will have knowledge of Remote Sensing and experience of using Remote Sensing and GIS software and be qualified to the corresponding level of the award as required to teach (or demonstrate equivalent professional/industry level experience). Further to the person specification, teaching and research experience in the following areas is strongly desirable: Managing and processing remote sensing data. Utilising remote sensing data to inform modelling environmental dynamics. Environmental Image processing and analysis. Modelling land cover change using machine learning. Please refer to the person specification (available on the university's website, accessed by the 'Apply' button) for further selection criteria. Remuneration: Payment is based on an hourly rate depending on length of continuous service with the College, starting rate £71.07 per hour inclusive of pro-rata London Allowance and holiday pay, for contact hours worked. This hourly rate is based on the starting point of Grade 7 and is inclusive of a ‘Duties Related to Teaching Multiplier’ at 2.5, which covers preparation, teaching, administration, assessment marking and other examining duties in connection with the course. Contract: Fixed-term, part-time contract teaching. Please submit a CV for consideration. Closing date: Sunday, 1 November, interview date: Wednesday, 18 November 2026. Enquiries: If you would like to know more about the role, please click on apply below or contact Shino Shiode at [email protected]. If you have technical issues or difficulties using the recruitment portal, please contact [email protected], providing your name and the job reference number of the position. While we are happy to respond to all informal enquiries, only formal applications through the online system will be considered. We welcome applicants from all sections of the community. The College is committed to improving the gender and cultural diversity of its workforce, holding an Athena SWAN award and operating Disability Confident & Mindful Employer schemes.",
"description_full": "Birkbeck, University of London, has an opportunity for an Associate Lecturer to join the teaching team and support the School of Social Sciences this coming Spring 2027.\nWe are seeking an Associate Lecturer to teach on the following module:\nUnderstanding Environment Using GIS and Remote Sensing (30 hours) Thursdays, 14 January to 25 March 2027.\nYou will have knowledge of Remote Sensing and experience of using Remote Sensing and GIS software and be qualified to the corresponding level of the award as required to teach (or demonstrate equivalent professional/industry level experience).\nFurther to the person specification, teaching and research experience in the following areas is strongly desirable:\nManaging and processing remote sensing data.\nUtilising remote sensing data to inform modelling environmental dynamics.\nEnvironmental Image processing and analysis.\nModelling land cover change using machine learning.\nPlease refer to the person specification (available on the university's website, accessed by the 'Apply' button) for further selection criteria.\nRemuneration:\nPayment is based on an hourly rate depending on length of continuous service with the College, starting rate £71.07 per hour inclusive of pro-rata London Allowance and holiday pay, for contact hours worked.\nThis hourly rate is based on the starting point of Grade 7 and is inclusive of a ‘Duties Related to Teaching Multiplier’ at 2.5, which covers preparation, teaching, administration, assessment marking and other examining duties in connection with the course.\nContract:\nFixed-term, part-time contract teaching. Please submit a CV for consideration. Closing date: Sunday, 1 November, interview date: Wednesday, 18 November 2026.\nEnquiries:\nIf you would like to know more about the role, please click on apply below or contact Shino Shiode at [email protected].\nIf you have technical issues or difficulties using the recruitment portal, please contact [email protected], providing your name and the job reference number of the position.\nWhile we are happy to respond to all informal enquiries, only formal applications through the online system will be considered.\nWe welcome applicants from all sections of the community. The College is committed to improving the gender and cultural diversity of its workforce, holding an Athena SWAN award and operating Disability Confident & Mindful Employer schemes.",
"description_html": "\n <p>Birkbeck, University of London, has an opportunity for an Associate Lecturer to join the teaching team and support the <a href=\"https://www.bbk.ac.uk/school/social-sciences\" target=\"_blank\" rel=\"noreferrer noopener\">School of Social Sciences</a> this coming Spring 2027.</p>\n<p>We are seeking an Associate Lecturer to teach on the following module:</p>\n<p><strong>Understanding Environment Using GIS and Remote Sensing (30 hours) </strong>Thursdays, 14 January to 25 March 2027.</p>\n<p>You will have knowledge of Remote Sensing and experience of using Remote Sensing and GIS software and be qualified to the corresponding level of the award as required to teach (or demonstrate equivalent professional/industry level experience).</p>\n<p>Further to the person specification, teaching and research experience in the following areas is strongly desirable:</p>\n<ul>\n<li>Managing and processing remote sensing data.</li>\n<li>Utilising remote sensing data to inform modelling environmental dynamics.</li>\n<li>Environmental Image processing and analysis.</li>\n<li>Modelling land cover change using machine learning.</li>\n</ul>\n<p>Please refer to the person specification (available on the university's website, accessed by the 'Apply' button) for further selection criteria.</p>\n<p><strong>Remuneration</strong>:<br/>Payment is based on an hourly rate depending on length of continuous service with the College, starting rate £71.07 per hour inclusive of pro-rata London Allowance and holiday pay, for contact hours worked.</p>\n<p>This hourly rate is based on the starting point of Grade 7 and is inclusive of a ‘Duties Related to Teaching Multiplier’ at 2.5, which covers preparation, teaching, administration, assessment marking and other examining duties in connection with the course.</p>\n<p><strong>Contract</strong>:<br/>Fixed-term, part-time contract teaching. Please submit a CV for consideration. <strong>Closing date: Sunday, 1 November, interview date: Wednesday, 18 November 2026.</strong></p>\n<p><strong>Enquiries:<br/></strong>If you would like to know more about the role, please click on apply below or contact Shino Shiode at <a href=\"mailto:[email protected]\" target=\"_blank\" rel=\"noreferrer noopener\">[email protected]</a>.</p>\n<p>If you have technical issues or difficulties using the recruitment portal, please contact <a href=\"mailto:[email protected]\" target=\"_blank\" rel=\"noreferrer noopener\">[email protected]</a>, providing your name and the job reference number of the position.</p>\n<p>While we are happy to respond to all informal enquiries, only formal applications through the online system will be considered.</p>\n<p>We welcome applicants from all sections of the community. The College is committed to improving the gender and cultural diversity of its workforce, holding an Athena SWAN award and operating Disability Confident & Mindful Employer schem<em>es.</em></p> \n \n <div class=\"row-10 sub-grid sub-grid--centered \">\n </div>\n ",
"description_md": "Birkbeck, University of London, has an opportunity for an Associate Lecturer to join the teaching team and support the [School of Social Sciences](https://www.bbk.ac.uk/school/social-sciences) this coming Spring 2027.\n\nWe are seeking an Associate Lecturer to teach on the following module:\n\n**Understanding Environment Using GIS and Remote Sensing (30 hours)**Thursdays, 14 January to 25 March 2027.\n\nYou will have knowledge of Remote Sensing and experience of using Remote Sensing and GIS software and be qualified to the corresponding level of the award as required to teach (or demonstrate equivalent professional/industry level experience).\n\nFurther to the person specification, teaching and research experience in the following areas is strongly desirable:\n\n- Managing and processing remote sensing data.\n- Utilising remote sensing data to inform modelling environmental dynamics.\n- Environmental Image processing and analysis.\n- Modelling land cover change using machine learning.\n\nPlease refer to the person specification (available on the university's website, accessed by the 'Apply' button) for further selection criteria.\n\n**Remuneration**:\nPayment is based on an hourly rate depending on length of continuous service with the College, starting rate £71.07 per hour inclusive of pro-rata London Allowance and holiday pay, for contact hours worked.\n\nThis hourly rate is based on the starting point of Grade 7 and is inclusive of a ‘Duties Related to Teaching Multiplier’ at 2.5, which covers preparation, teaching, administration, assessment marking and other examining duties in connection with the course.\n\n**Contract**:\nFixed-term, part-time contract teaching. Please submit a CV for consideration. **Closing date: Sunday, 1 November, interview date: Wednesday, 18 November 2026.**\n\n**Enquiries:**If you would like to know more about the role, please click on apply below or contact Shino Shiode at [[email protected]](mailto:[email protected]).\n\nIf you have technical issues or difficulties using the recruitment portal, please contact [[email protected]](mailto:[email protected]), providing your name and the job reference number of the position.\n\nWhile we are happy to respond to all informal enquiries, only formal applications through the online system will be considered.\n\nWe welcome applicants from all sections of the community. The College is committed to improving the gender and cultural diversity of its workforce, holding an Athena SWAN award and operating Disability Confident & Mindful Employer schem*es.*",
"posted_at": "2026-10-22",
"posted_at_text": "22 Oct",
"posted_at_datetime": "2026-10-22",
"closing_at": "2026-11-01",
"job_url": "https://www.jobs.ac.uk/job/DTJ141/associate-lecturer-in-geographic-data-science",
"application_url": "https://www.jobs.ac.uk/job/DTJ141/associate-lecturer-in-geographic-data-science",
"source_platform": "jobs.ac.uk",
"position_type": "academic",
"academic_rank": "Lecturer",
"research_field": "Data Science",
"funding_source": null,
"stipend_amount_gbp": null,
"duration_years": null,
"supervisor_name": null,
"search_query": "lecturer",
"detail_status": "ok",
"scraped_at": "2026-10-22T08:47:29Z",
"contact_emails": [],
"contact_phones": [],
"contact_urls": [],
"company_about": null,
"company_phone": null,
"company_email": null,
"company_website": "http://www.bbk.ac.uk",
"company_address_street": null,
"company_address_city": "London",
"company_address_postcode": null,
"company_address_country": "United Kingdom",
"company_active_jobs_count": 0,
"company_active_jobs": null
}Priced at $0.0050 per company detail result. 10 company detail results ≈ $0.05, 100 ≈ $0.50, 1,000 ≈ $5.00. The first runs land inside Apify's $5/mo free-tier credit — pay only for what you extract, no monthly subscription.
Click Open on Apify above to run jobs-ac-uk-scraper in your browser - no code, no install. In the Apify console you get:
To run this actor from your own code you need an Apify API token. Get one in about a minute:
Free tier: Apify credits your account with $5 of platform usage every month, no credit card required. Enough to test any actor meaningfully. How many results that covers depends on the actor's price per result.
Run this actor from any language via the Apify REST API. Replace YOUR_TOKEN with your API token and adapt the input JSON to your needs.
curl -X POST "https://api.apify.com/v2/acts/santamaria-automations~jobs-ac-uk-scraper/run-sync-get-dataset-items?token=YOUR_TOKEN" \
-H "Content-Type: application/json" \
-d '{}'// npm install apify-client
import { ApifyClient } from 'apify-client';
const client = new ApifyClient({ token: 'YOUR_TOKEN' });
const run = await client.actor('santamaria-automations/jobs-ac-uk-scraper').call({});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);# pip install apify-client
from apify_client import ApifyClient
client = ApifyClient('YOUR_TOKEN')
run = client.actor('santamaria-automations/jobs-ac-uk-scraper').call(run_input={})
items = list(client.dataset(run['defaultDatasetId']).iterate_items())
print(items)// dotnet add package Apify.Client
using Apify.Client;
var client = new ApifyClient("YOUR_TOKEN");
var run = await client.Actor("santamaria-automations/jobs-ac-uk-scraper").CallAsync(new { });
var items = await client.Dataset(run.DefaultDatasetId).ListItemsAsync();// Maven: com.apify:apify-client
import com.apify.client.ApifyClient;
ApifyClient client = new ApifyClient("YOUR_TOKEN");
ActorRun run = client.actor("santamaria-automations/jobs-ac-uk-scraper").call(Map.of());
List<Map<String,Object>> items = client.dataset(run.getDefaultDatasetId()).listItems();This actor is available on the Apify MCP server, so you can drive it from any MCP-compatible AI client - Claude Desktop, Claude.ai, Cursor, VS Code, LangChain, LlamaIndex, or a custom agent - without writing any code.
https://mcp.apify.com?tools=santamaria-automations/jobs-ac-uk-scraperExample prompt once connected:
"Use <code>jobs-ac-uk-scraper</code> to run a scrape on my target list and give me the results as a table."
Clients that support dynamic tool discovery (Claude.ai, VS Code) receive the full input schema automatically via add-actor.
Trigger this actor from your favorite automation tool. Every platform below can call the Apify API in a few clicks - no code required.
@apify/n8n-nodes-apify).santamaria-automations/jobs-ac-uk-scraper.https://api.apify.com/v2/acts/santamaria-automations~jobs-ac-uk-scraper/run-sync-get-dataset-items?token=YOUR_TOKEN.application/json.https://api.apify.com/v2/acts/santamaria-automations~jobs-ac-uk-scraper/run-sync-get-dataset-items?token=YOUR_TOKEN, method POST, body raw JSON.https://api.apify.com/v2/acts/santamaria-automations~jobs-ac-uk-scraper/run-sync-get-dataset-items?token=YOUR_TOKEN.steps.http.$return_value in subsequent steps.https://api.apify.com/v2/acts/santamaria-automations~jobs-ac-uk-scraper/run-sync-get-dataset-items?token=YOUR_TOKEN, body type JSON.$5.00 / 1,000 company detail result, billed per result on Apify. Apify's $5/month free tier covers the first runs. No monthly subscription — you only pay for what you extract.
46 fields per result. Full field catalog is listed in the 'What you can scrape' table above — includes core identifiers, descriptive text, dates, and any category-specific data.
Scraping publicly available data is generally permitted in most jurisdictions, but GDPR applies to any personal data you collect. Review your local rules and consult a lawyer for commercial use.
No. This actor reads public pages over HTTP with datacenter proxies, switching to residential proxies only when a request is blocked. No API key, no OAuth, no rate-limit management on your side.
Every run pulls live data at execution time. Set up a schedule (daily/hourly/weekly cron) in the Apify console to keep your dataset current automatically.