diff --git a/src/eva/vision/data/wsi/patching/samplers/_utils.py b/src/eva/vision/data/wsi/patching/samplers/_utils.py
index af8418df..f1fa3b7e 100644
--- a/src/eva/vision/data/wsi/patching/samplers/_utils.py
+++ b/src/eva/vision/data/wsi/patching/samplers/_utils.py
@@ -1,14 +1,8 @@
-import random
 from typing import Tuple
 
 import numpy as np
 
 
-def set_seed(seed: int) -> None:
-    random.seed(seed)
-    np.random.seed(seed)
-
-
 def get_grid_coords_and_indices(
     layer_shape: Tuple[int, int],
     width: int,
@@ -33,8 +27,8 @@ def get_grid_coords_and_indices(
 
     indices = list(range(len(x_y)))
     if shuffle:
-        set_seed(seed)
-        np.random.shuffle(indices)
+        random_generator = np.random.default_rng(seed)
+        random_generator.shuffle(indices)
     return x_y, indices
 
 
diff --git a/src/eva/vision/data/wsi/patching/samplers/random.py b/src/eva/vision/data/wsi/patching/samplers/random.py
index 09ae5729..b37a3a3e 100644
--- a/src/eva/vision/data/wsi/patching/samplers/random.py
+++ b/src/eva/vision/data/wsi/patching/samplers/random.py
@@ -18,6 +18,7 @@ def __init__(self, n_samples: int = 1, seed: int = 42):
         """Initializes the sampler."""
         self.seed = seed
         self.n_samples = n_samples
+        self.random_generator = random.Random(seed)  # nosec
 
     def sample(
         self,
@@ -33,9 +34,10 @@ def sample(
             layer_shape: The shape of the layer.
         """
         _utils.validate_dimensions(width, height, layer_shape)
-        _utils.set_seed(self.seed)
 
         x_max, y_max = layer_shape[0], layer_shape[1]
         for _ in range(self.n_samples):
-            x, y = random.randint(0, x_max - width), random.randint(0, y_max - height)  # nosec
+            x, y = self.random_generator.randint(0, x_max - width), self.random_generator.randint(
+                0, y_max - height
+            )
             yield x, y