The race condition in the provided code arises because multiple threads can access and modify the shared dictionaries `self.jobs` and `self.results` simultaneously without synchronization. Specifically, one thread might read a job while another thread deletes it, or multiple threads might attempt to process the same job or write to the results dictionary concurrently, leading to inconsistent states or exceptions.

To fix this, we need to use a `threading.Lock` to ensure that access to the shared state (`self.jobs` and `self.results`) is atomic.

Here is the complete fixed implementation:

```python
import threading

class JobQueue:
    def __init__(self):
        self.jobs = {}
        self.results = {}
        # Initialize a lock to manage thread access to shared state
        self.lock = threading.Lock()

    def add_job(self, job_id, data):
        # Lock ensures that adding a job is thread-safe
        with self.lock:
            self.jobs[job_id] = data
        return job_id

    def process_job(self, job_id, processor):
        # Lock ensures that the check, processing, and cleanup are atomic.
        # This prevents multiple threads from processing the same job
        # and prevents race conditions when writing to self.results.
        with self.lock:
            if job_id not in self.jobs:
                return False

            data = self.jobs[job_id]
            
            # Execute the processor
            # Note: The lock is held during processing. 
            # For high-performance scenarios with long-running tasks, 
            # one might 'pop' the job here to release the lock, 
            # but that changes the semantics (job is lost if processor fails).
            result = processor(data)

            # Update results and remove the job from the active queue
            self.results[job_id] = result
            del self.jobs[job_id]
            
        return True

    def get_result(self, job_id):
        # Lock ensures consistent reading of results
        with self.lock:
            return self.results.get(job_id)
```

### Key Changes Made:
1.  **Added `self.lock = threading.Lock()`**: Initialized a lock object in the constructor.
2.  **Protected `add_job`**: Wrapped the dictionary update in `with self.lock` to prevent concurrent writes to `self.jobs`.
3.  **Protected `process_job`**: Wrapped the entire logic (check existence, retrieve data, process, write result, delete job) inside `with self.lock`. This ensures that:
    *   A job cannot be picked up by two threads simultaneously (preventing duplicate processing).
    *   The deletion from `self.jobs` and writing to `self.results` happen atomically.
    *   *Note:* The lock is held during the `processor(data)` execution. While this serializes processing, it is the safest fix that preserves the original logic (where the job remains in `self.jobs` until processing completes, allowing for potential retry logic on failure).
4.  **Protected `get_result`**: Wrapped the read operation in `with self.lock` to ensure thread-safe access to `self.results`.