...

Refresh Jupyter in your browser, you should now have your environment available as a kernel.

R Notebook

...

conda create --name <new_environment_for_R> --clone /albedo/soft/sw/conda-sw/jupyterhub-<newest_version_available>/

Then, activate your new environment and install the R packages you need, either with the R package manager or with conda (as in the following example)To create an R kernel for your own instance of Jupyter load the R module:

condamodule activate <new_environment_for_R>
conda install r-<my_package>load r

Then install the kernel with IRkernel, making sure you name it differently than just simply "R" (e.g. "my_R_kernel")Finally, create your new R kernel:

Rscript -e 'IRkernel::installspec(name="<new<your_environmentR_for_R>kernel>", displayname="<new<your_environmentR_for_R>kernel")'

Refresh Jupyter in your browser, you should now have your environment available as a kernel. Whatever you had installed in your instance of R should be available via that kernel's notebooks.

Singularity

...