diff --git a/notebooks/Tutorial/calversion.ipynb b/notebooks/Tutorial/calversion.ipynb
index 2ae7833374acabdc1cb83a5acf10085241849524..14933bab4ff9399154c657de68c43ae2f98dac2e 100644
--- a/notebooks/Tutorial/calversion.ipynb
+++ b/notebooks/Tutorial/calversion.ipynb
@@ -10,7 +10,29 @@
     "\n",
     "A small example how to adapt a notebook to run with the offline calibration package \"pycalibation\".\n",
     "\n",
-    "The first cell contains all parameters that should be exposed to the command line."
+    "The first cell contains all parameters that should be exposed to the command line.\n",
+    "\n",
+    "To run this notebooks with several different input parameters in parallel by submitting multiple slurm jobs, for example for various random seed we can do the following:\n",
+    "\n",
+    "xfel-calibrate TUTORIAL TEST --random-seed 1,2,3,4\n",
+    "\n",
+    "or\n",
+    "\n",
+    "xfel-calibrate TUTORIAL TEST --random-seed 1-5\n",
+    "\n",
+    "will produce 4 jobs:\n",
+    "\n",
+    "Parsed input 1,2,3,4 to [1, 2, 3, 4]\n",
+    "\n",
+    "Submitted job: 1169340\n",
+    "\n",
+    "Submitted job: 1169341\n",
+    "\n",
+    "Submitted job: 1169342\n",
+    "\n",
+    "Submitted job: 1169343\n",
+    "\n",
+    "Submitted the following SLURM jobs: 1169340,1169341,1169342,1169343"
    ]
   },
   {
@@ -23,7 +45,7 @@
    "source": [
     "out_folder = \"/gpfs/exfel/data/scratch/amunnich/tutorial\" # output folder\n",
     "sensor_size = [10, 30] # defining the picture size\n",
-    "random_seed = 2345 # random seed for filling of fake data array. Change it to produce different results.\n",
+    "random_seed = [2345] # random seed for filling of fake data array. Change it to produce different results, range allowed\n",
     "runs = 500 # how may iterations to fill histograms\n",
     "cluster_profile = \"tutorial\" "
    ]
@@ -32,7 +54,8 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "First include what we need and set up the cluster profile. Everything that has a written response in a cell will show up in the report, e.g. prints but also return values or errors."
+    "First include what we need and set up the cluster profile for parallel processing on one node utilising more than one core.\n",
+    "Everything that has a written response in a cell will show up in the report, e.g. prints but also return values or errors."
    ]
   },
   {
@@ -105,16 +128,19 @@
    },
    "outputs": [],
    "source": [
+    "# in order to run several random seeds in parallel the parameter has to be a list. To use the current single value in this \n",
+    "# notebook we use the first entry in the list\n",
+    "random_seed_single = random_seed[0]\n",
     "fake_data = []\n",
     "for i in range(runs):\n",
-    "    fake_data.append(data_creation(random_seed+10*i))"
+    "    fake_data.append(data_creation(random_seed_single+10*i))"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Plot the random image. everything we write here in the markup cells will show up as text in the report."
+    "Create some random images and plot them. Everything we write here in the markup cells will show up as text in the report."
    ]
   },
   {
@@ -183,7 +209,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "To parallelise jobs we use the ipyparallel client."
+    "To parallelise jobs we use the ipyparallel client. This will run on one node an ipcluster with the specified number of cores given in xfel_calibrate/notebooks.py."
    ]
   },
   {
diff --git a/xfel_calibrate/notebooks.py b/xfel_calibrate/notebooks.py
index a0e78baa11d69a58a3573388ac190f7882218800..43cd62ad8cb1d9fadb609fd12d8423874b1af801 100644
--- a/xfel_calibrate/notebooks.py
+++ b/xfel_calibrate/notebooks.py
@@ -84,7 +84,7 @@ notebooks = {
             "TUTORIAL": {
                        "TEST": {
                                "notebook": "notebooks/Tutorial/calversion.ipynb",
-                               "concurrency": {"parameter": None,
+                               "concurrency": {"parameter": "random_seed",
                                                "default concurrency": None,
                                                "cluster cores": 32},
                                },