Here is the complete fixed implementation of the `JobQueue` class with proper concurrency handling:

```python
import threading

class JobQueue:
    def __init__(self):
        self.jobs = {}
        self.results = {}
        self.lock = threading.Lock()

    def add_job(self, job_id, data):
        """Add a new job to the queue."""
        with self.lock:
            self.jobs[job_id] = data
        return job_id

    def process_job(self, job_id, processor):
        """Process a job if it exists in the queue."""
        with self.lock:
            if job_id not in self.jobs:
                return False

            data = self.jobs[job_id]
            result = processor(data)

            self.results[job_id] = result
            del self.jobs[job_id]
        return True

    def get_result(self, job_id):
        """Retrieve the result of a job."""
        with self.lock:
            return self.results.get(job_id)
```

### Key Fixes:

1. **Thread Safety**: A `threading.Lock` is introduced to protect all access to shared state (`self.jobs` and `self.results`).
2. **Atomic Operations**: Each method uses the lock to ensure that all operations on shared data structures are atomic.
3. **Race Condition Eliminated**: The original race condition—where multiple threads could concurrently write to `self.results`—is now prevented by serializing access to the shared state.
4. **Consistent Locking**: All methods that read or write shared state are protected by the same lock, preventing interleaved operations and ensuring data consistency.

This implementation ensures thread-safe job queue operations in a multi-threaded environment.