diff --git a/.env.example b/.env.example
index 32cb42d..57c216c 100644
--- a/.env.example
+++ b/.env.example
@@ -23,3 +23,5 @@ MAX_TIME_CPU="1:00:00"
 PARTITIONS_GPU='["p_gpu1", "p_gpu2"]'
 RESERVATIONS_GPU='["r_gpu1", "r_gpu2"]'
 MAX_TIME_GPU="1:00:00"
+SUBMISSION_SSH_KEY="~/.ssh/id_rsa"
+FORWARD_PORTS='["8888:8888"]'
diff --git a/docker-compose.yml b/docker-compose.yml
index 85b7ae8..39b17a8 100644
--- a/docker-compose.yml
+++ b/docker-compose.yml
@@ -25,6 +25,8 @@ services:
       PARTITIONS_GPU: "${PARTITIONS_GPU}"
       RESERVATIONS_GPU: "${RESERVATIONS_GPU}"
       MAX_TIME_GPU: "${MAX_TIME_GPU}"
+      SUBMISSION_SSH_KEY: "${SUBMISSION_SSH_KEY}"
+      FORWARD_PORTS: "${FORWARD_PORTS}"
     volumes:
       - $READ_DIR:/app/work/data
       - $WRITE_DIR:/app/work/mlex_store
diff --git a/src/frontend.py b/src/frontend.py
index cb1efb0..bc84a70 100755
--- a/src/frontend.py
+++ b/src/frontend.py
@@ -46,12 +46,14 @@
 FLOW_TYPE = os.getenv("FLOW_TYPE", "podman")
 
 # Slurm
-PARTITIONS_CPU = os.getenv("PARTITIONS_CPU", [])
-RESERVATIONS_CPU = os.getenv("RESERVATIONS_CPU", [])
+PARTITIONS_CPU = json.loads(os.getenv("PARTITIONS_CPU", []))
+RESERVATIONS_CPU = json.loads(os.getenv("RESERVATIONS_CPU", []))
 MAX_TIME_CPU = os.getenv("MAX_TIME_CPU", "1:00:00")
-PARTITIONS_GPU = os.getenv("PARTITIONS_CPU", [])
-RESERVATIONS_GPU = os.getenv("RESERVATIONS_CPU", [])
+PARTITIONS_GPU = json.loads(os.getenv("PARTITIONS_CPU", []))
+RESERVATIONS_GPU = json.loads(os.getenv("RESERVATIONS_CPU", []))
 MAX_TIME_GPU = os.getenv("MAX_TIME_CPU", "1:00:00")
+SUBMISSION_SSH_KEY = os.getenv("SUBMISSION_SSH_KEY", "")
+FORWARD_PORTS = json.loads(os.getenv("FORWARD_PORTS", []))
 
 # Mlex content api
 CONTENT_API_URL = os.getenv("CONTENT_API_URL", "http://localhost:8000/api/v0/models")
@@ -99,6 +101,8 @@
                 "reservations": RESERVATIONS_CPU,
                 "max_time": MAX_TIME_CPU,
                 "conda_env_name": "mlex_dimension_reduction_pca",
+                "submission_ssh_key": SUBMISSION_SSH_KEY,
+                "forward_ports": FORWARD_PORTS,
                 "params": {
                     "io_parameters": {"uid_save": "uid0001", "uid_retrieve": ""}
                 },
@@ -366,18 +370,21 @@ def submit_dimension_reduction_job(
             }
         elif FLOW_TYPE == "conda":
             autoencoder_params = {
-                "conda_env_name": "pytorch_autoencoders",
+                "conda_env_name": "mlex_pytorch_autoencoders",
                 "params": auto_params,
                 "python_file_name": "mlex_pytorch_autoencoders/src/predict_model.py",
             }
-        else:
+        else:  # slurm
             autoencoder_params = {
                 "job_name": "latent_space_explorer",
                 "num_nodes": 1,
                 "partitions": PARTITIONS_GPU,
                 "reservations": RESERVATIONS_GPU,
                 "max_time": MAX_TIME_GPU,
-                "conda_env_name": "pytorch_autoencoders",
+                "conda_env_name": "mlex_pytorch_autoencoders",
+                "python_file_name": "mlex_pytorch_autoencoders/src/predict_model.py",
+                "submission_ssh_key": SUBMISSION_SSH_KEY,
+                "forward_ports": FORWARD_PORTS,
                 "params": auto_params,
             }
         job_params["params_list"].insert(0, autoencoder_params)