SLURM script to run indefinitely to avoid session timeout - ssh

Question

Background:
I need to remote access a HPC across the country (place is closed for public, I am interning for the summer)
Once I accomplish this, I load a script, for this purpose let's call it jupyter.sh
There are several nodes in this HPC, and every time I run the .sh script, I get assigned to one, say N123
From Jupyter notebook on browser, I have to run actual code/ calculations/ simulations using python. The data I'm working with takes about 2 hours to run completely so that I can then process it and do my job
Very often, I would get disconnected from that node N123 because "user doesn't have an active job running", even though my jupyter notebook is still running / I'm working on it
This results in me having to run that .sh script again, meaning I will get a different node, say N456 (then the ssh command line for jupyter has to be entered again, this time with the different node number)
Jupyter will disconnect from host, and this forces me to restart kernel and run the entire code again, costing me that 1 hour and something it takes to run the python code.
(Can't get into too many details since I don't know what I am allowed to share without getting in trouble)
My question is,
Is there a way that i can run an sh script with say, an infinite loop, so that the node sees it as an active job running and it doesn't kick me out for "inactivity" ?
I have tried running different notebooks that take about 10 minutes total to run, but this doesn't seem to be enough to be considered an active job (and I am not sure if it even counts)
My experience with slurm, terminal and ssh processes is very limited, so if this is a silly question, please forgive.
Any help is appreciated.
#!/bin/bash
#SBATCH --nodes=1
#SBATCH --tasks-per-node=1
#SBATCH --job-name=pytorch
#SBATCH --mail-type=ALL
#SBATCH --mail-user== NO NEED TO SEE THIS
#SBATCH --partition=shared-gpu
#SBATCH --qos=long
#SBATCH --ntasks=1
#SBATCH --mem=2G
#SBATCH --time=04:00:00
export PORT=8892
kill -9 $(lsof -t -i:$PORT)
# Config stuff
module purge
module load anaconda/Anaconda3
module load cuda/10.2
source activate NO NEED FOR THIS
# Print stuff
echo Working directory is $SLURM_SUBMIT_DIR
cd $SLURM_SUBMIT_DIR
echo Running on host `hostname`
echo Time is `date`
### Define number of processors
echo This job has allocated $SLURM_JOB_NUM_NODES nodes
# Tell me which nodes it is run on
echo " "
echo This jobs runs on the following processors:
echo $SLURM_JOB_NODELIST
echo " "
jupyter notebook --no-browser --port=$PORT
echo Time is `date

Answer 1

Would something like:
#!/bin/bash
#SBATCH --job-name=jupyter # Job name
#SBATCH --nodes=1 # Run all processes on a single node.
#SBATCH --ntasks=1 # Run a single task
#SBATCH --cpus-per-task=1 # Number of CPU cores per task (multithreaded tasks)
#SBATCH --mem=2G # Job memory request. If you do not ask for enough your program will be killed.
#SBATCH --time=04:00:00 # Time limit hrs:min:sec. If your program is still running when this timer ends it will be killed.
srun jupyter.sh
work? You write this up in a text editor, save it as .slurm, then run it using
sbatch jobname.slurm
Salloc might also be a good way to go about this.