There has been some rumors for the past few months of a voluntary separation or layoffs at LANL. On the face of it they do not seem very likely as Mason said budget wise things look good. However Mason also said that the lab needs to reduce indirect costs. I guess this has something to do with fear of Doge and reduction of overheard rates. NSF and NIH have been seen as having way to high of overhead so it seems like DOE/NNSA labs could be next. In fact there was story the other day about DOE money overhead rates needing to be cut (see link below).
This is what I think may actually be possible. DOE/NNSA will be told you need to reduce overheard or indirect costs , so they will not be able to put everybody on direct costs so they will have to let people go one way or another. Indirect costs is of course management , admins, outreach and such but also LDRD.
Here is the link on DOE cutting university overheard rates to 15%. It could be that the will do the same for NNSA. I doubt an overheard rate of only 15% is feasible because we do not have students paying tuition but they could still ask for a big cut in overheard at the NNSA labs. 50% of the lab budget is indirect right now if we have to cut 25% of our overhead rate than a layoff of 10-15% of the lab workforce could be possible. Of course it also means that LANL looks horrible because for the past 6 years we have been told to hire, hire , hire. Interview 50, hire 50 and grow. There was even some voices who said that we should not get ahead of ourselves because we do know what the next administration may want.
https://www.science.org/content/article/energy-department-cuts-university-overhead-rates-to-15-on-research-grants
Comments
I agree but I think they run into all sorts of violations if you cut " army of regulatory compliance and safety people." I think you need to change the rules and regulations of NNSA before you change this. The mass overheard is driven by crazy rules. If they violate a rule it just costs huge amounts of money. There is huge bloat in the system but unless some higher ups change some of the rules, regulations and so on I do not see how you get rid of it.
I see lots of ways of this going wrong. However if they randomly did get rid of half the workforce and insisted the rest people work 8 hours a day I think it would not be that different. You have have do some reorganization but I doubt you would see much drop in actual work done. The big thing I notice and this is even well before Covid is the lack of people working their hours.
I hope the labs will sincerely review past EIT tragedies, and move to treat employees with the dignity and respect they deserve.
For the support staff I have heard that they're unofficial Dons in Espanola that get you the job in Los Alamos. It is pretty much village politics.
Livermore is losing support staff due to wages for the support staff not keeping up with the Tech wages / housing costs. A few of my Techs/ machinists that supported my projects were in this situation and I told them to apply at LANL and they all never got a reply and ended up leaving DOE. Meanwhile we have a backlog of projects waiting on classified manufacturing support. While I have better luck getting support from LANL than SMMF this is affecting the programs. greatly. Meanwhile still waiting on SNL and KC for delivery as well, so this is a complex wide problem now. The director at LLNL just said her idea was to use AI and AM to deliver manufacturing support.. I guess she worked on a different tolerance band than our NNSA requirements.
At LANL the manages keep going on this weird AI mantra that it will do all of science, and save the lab, speed things up by 100 fold. So far nothing, I get the feeling they really have no idea what AI is and think that if it can write a mindless empty memo faster that it must be able to do everything. It is off the wall seeing them talk about AI and getting everything wrong. It is just repeats of the what you see on CNN which lacks depth, is just crazy wrong, not AI. For example they keep saying quantum computing is AI. Not AI, that protein folding was solved by ChatGP, protein folding was a solved and the results they are talking about are not even a language model. It just goes on and on. Now even the LLNL lab director is saying this crap?