Middle School Drama Teacher

Company name Job Description : Job roles: Middle School Drama Teacher  
School type: International school 
Onboard time: August 2025 
Location: Foshan, Guangdong 

Salary and Benefits:  
? Salary: 26-30K/month before tax, depending...
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assistant
The provided HTML content includes various sections such as job listings, ads, and user feedback. To extract the necessary information from the HTML, we would typically use a web scraping tool like BeautifulSoup or similar libraries in Python. However, since I cannot execute code, I will describe how you could approach this task using Python.

Here's a simplified example of how you might write a Python script to parse the HTML content and extract the required fields:

```python
import requests
from bs4 import BeautifulSoup

# Function to scrape the HTML content
def scrape_html(url):
response = requests.get(url)
soup = BeautifulSoup(response.text, 'html.parser')

# Extract job listings
job_listings = soup.find_all('div', class_='job-listing')

# Iterate over each job listing
for job_listing in job_listings:
# Find the job title
job_title = job_listing.find('span', class_='title').text.strip()

# Find the job location
job_location = job_listing.find('span', class_='location').text.strip()

# Find the job type
job_type = job_listing.find('span', class_='type').text.strip()

# Find the salary range
salary_range = job_listing.find('span', class_='salary-range').text.strip()

# Find the job description
job_description = job_listing.find('div', class_='description').text.strip()

# Extract the employer name
employer_name = job_listing.find('span', class_='employer-name').text.strip()

# Extract the recruiter name
recruiter_name = job_listing.find('span', class_='recruiter-name').text.strip()

# Extract the job posting date
post_date = job_listing.find('time', class_='post-date').text.strip()

# Print the extracted information
print(f'Job