diff --git a/bind/G4Calo.py b/bind/G4Calo.py
index c2eed20..68a90ec 100644
--- a/bind/G4Calo.py
+++ b/bind/G4Calo.py
@@ -152,8 +152,9 @@ def _run_mini_batch(
     from  G4Calo import __G4System
     G4System = __G4System()
     seed = int(batch_seed + counter)
-    #truncate to 32 bit, lower 32 bit are used in G4
-    seed = seed & 0xFFFFFFFF
+        
+    print(f"Running mini batch with seed {seed}")
+    
     G4System.init(cw, seed) #counter gives random seed offset
 
     df = G4System.run_batch(nEvents, particleSpec, minEnergy_GeV, maxEnergy_GeV,"")
@@ -188,8 +189,11 @@ def run_batch(
     
     nevents = [nEventsPerCore if i < nCores - 1 else nEventsLastCore for i in range(nCores)]
 
-    batch_seed = int(time.time()*1000)
-
+    batch_seed = int(time.time()) #this is seconds
+    # make sure that the seed is different for next run. This is not perfect but should be good enough
+    # given the course takes a week this should be sufficient (10^7 seconds ~ 4 months)
+    time.sleep(1) 
+    batch_seed = batch_seed % 10000000
     print(f"Batch seed: {batch_seed}")
     #use a multiprocessing pool to run the mini batches in parallel
     with multiprocessing.Pool(nCores) as pool: