Fully funded doctoral student positions in Finland

There is a new government funded Finnish Doctoral Program in AI. Research topics include Bayesian inference, modeling and workflows as part of fundamental AI. There is a big joint call, where you can choose the supervisor you want to work with. I (Aki) am also one of the supervisors. Come work with me or share the news! The first call deadline is April 2, and the second call deadline in fall 2024. See how to apply at https://fcai.fi/doctoral-program, and more about my research at my web page.

It’s bezzle time: The Dean of Engineering at the University of Nevada gets paid $372,127 a year and wrote a paper that’s so bad, you can’t believe it.

“As we look to sleep and neuroscience for answers we can study flies specifically the Drosophila melanogaster we highlight in our research.”

1. The story

Someone writes:

I recently read a paper of yours in the Chronicle about how academic fraudsters get away with it. I came across a strange case that I thought you would at least have some interest in when a faculty members owns an open access journal that costs to publish and then publishes a large number of papers in the journal.  The most recent issue is all from the same authors (family affair).

It is from an administrator at University of Nevada Reno.  This concern is related to publications within a journal that may not be reputable.   The Dean of Engineering has a number of publications in the International Supply Chain Technology Journal that are in question Google Scholar.  Normally, I would contact the editor, or publisher, but in this case, there are complexities.

This may not  be an issue but many of the articles are short, being 1 or 2 pages. In addition, some have a peer review process of 3 days or less. Another concern is that many of the papers do not even discuss what is in the title.  Take the following paper: It presents nothing about the title. Many of the papers read as if AI was used.

While the quality of these papers may not be of concern, the representation of these as publications could be. The person publishing them should have ethical standards that exceed those that are under his leadership. He is also the highest ranking official of the college of engineering and is expected to lead by example and be a good model to those under him.

If that is not enough, looking into the journal in more detail alludes to more ethical questions. The journal is published by PWD Group out of Texas. Lookup of PWD Group out of Texas yields that Erick Jones is the Director and President.  Erick Jones was also the Editor of the journal.  In addition to the journal articles, even books authored by Erick Jones are published by PWD.

Further looking into the journal publications you will see that there are a large number with Erick Jones Sr. and Erick Jones Jr.  There are also a large number with Felicia Jefferson.  Felicia is also a faculty member at UNR and the spouse of Dean Jones.  A few of the papers raise concerns related to deer supply chains. The following has a very fast peer review process of a few days and the caption of a white tailed deer is a reindeer. Another paper is even shorter, with a very fast peer review, and captions yet a different deer which is still not a white tail. It is unlikely these papers went through a robust peer review.

While these papers affiliation are prior to coming to UNR, the incoherence, conflict of interest, and incorrect data do lot look good for UNR and they were published either when Dr. Jefferson was applying to UNR or early upon her arrival. Similar issues with the timing of this article. Also, in the print version of the journal, Dr. Jefferson handles submissions (pp3).

Maybe this information is nothing to be concerned about.  At the very least, it sheds a poor light on the scientific process, especially when a Dean is the potential abuser.  It is not clear how he can encourage high quality manuscripts from other faculty when he has been able to climb the ladder using his own publishing house. I’ll leave you with a paper with a relevant title on minimizing train accidents through minimizing sleep deprivation. It seems like a really important study.  The short read should convince you otherwise and make you question the understanding of the scientific process by these authors.

Of specific concern is whether these publications led to he, or his spouse, being hired at UNR.  If these are considered legitimate papers, the entire hiring and tenure process at UNR is compromised.  Similar arguments exist if these papers are used in the annual evaluation process. It also raises a conflict of interest if he pays to publish and then receives proceeds on the back end.

I have no comment on the hiring, tenure, and evaluation process at UNR, or on any conflicts of interest. I know nothing about what is going on at UNR. It’s a horrifying story, though.

2. The published paper

OK, here it is, in its entirety (except for references). You absolutely have to see it to believe it:

Compared to this, the Why We Sleep guy is a goddamn titan of science.

3. The Dean of Engineering

From the webpage of the Dean of Engineering at the University of Reno:

Dr. Erick C. Jones is a former senior science advisor in the Office of the Chief Economist at the U.S. State Department. He is a former professor and Associate Dean for Graduate Studies at the College of Engineering at The University of Texas at Arlington.

From the press release announcing his appointment, dated July 01, 2022:

Jones is an internationally recognized researcher in industrial manufacturing and systems engineering. . . . “In Erick Jones, our University has a dynamic leader who understands how to seize moments of opportunity in order to further an agenda of excellence,” University President Brian Sandoval said. . . . Jones was on a three-year rotating detail at National Science Foundation where he was a Program Director in the Engineering Directorate for Engineering Research Centers Program. . . .

Jones is internationally recognized for his pioneering work with Radio Frequency Identification (RFID) technologies, Lean Six Sigma Quality Management (the understanding of whether a process is well controlled), and autonomous inventory control. He has published more than 243 manuscripts . . .

According to this source, his salary in 2022 was $372,127.

According to wikipedia, UNR is the state’s flagship public university.

I was curious to see what else Jones had published so I searched him on Google scholar and took a look at his three most-cited publications. The second of these appeared to be a textbook, and the third was basically 8 straight pages of empty jargon—ironic that a journal called Total Quality Management would publish something that has no positive qualities! The most-cited paper on the list was pretty bad too, an empty bit of make-work, the scientific equivalent of the reports that white-collar workers need to fill out and give to their bosses who can then pass these along to their bosses to demonstrate how productive they are. In short, this guy seems to be a well-connected time server in the Ed Wegman mode, minus the plagiarism.

He was a Program Director at the National Science Foundation! Your tax dollars at work.

Can you imagine what it would feel like to be a student in the engineering school at the flagship university of the state of Nevada, and it turns out the school is being run by the author of this:

Our recent study has the premise that both humans and flies sleep during the night and are awake during the day, and both species require a significant amount of sleep each day when their neural systems are developing in specific activities. This trait is shared by both species. An investigation was segmented into three subfields, which were titled “Life span,” “Time-to-death,” and “Chronological age.” In D. melanogaster, there was a positive correlation between life span, the intensity of young male medflies, and the persistence of movement. Time-to-death analysis revealed that the male flies passed away two weeks after exhibiting the supine behavior. Chronological age, activity in D. melanogaster was adversely correlated with age; however, there was no correlation between chronological age and time-to-death. It is probable that the incorporation the findings of age-related health factors and increased sleep may lead toless train accidents. of these age factors when considering these options supply chain procedure for maintaining will be beneficial.

I can’t even.

P.S. The thing I still can’t figure out is, why did Jones publish this paper at all? He’d already landed the juicy Dean of Engineering job, months before submitting it to his own journal. To then put his name on something so ludicrously bad . . . it can’t help his career at all, could only hurt. And obviously it’s not going to do anything to reduce train accidents. What was he possibly thinking?

P.P.S. I guess this happens all the time; it’s what Galbraith called the “bezzle.” We’re just more likely to hear about when it happens at some big-name place like Stanford, Harvard, Ohio State, or Cornell. It still makes me mad, though. I’m sure there are lots of engineers who are doing good work and could be wonderful teachers, and instead UNR spends $372,127 on this guy.

I’ll leave the last word to another UNR employee, from the above-linked press release:

“What is exciting about having Jones as our new dean for the College of Engineering is how he clearly understands the current landscape for what it means to be a Carnegie R1 ‘Very High Research’ institution,” Provost Jeff Thompson said. “He very clearly understands how we can amplify every aspect of our College of Engineering, so that we can continue to build transcendent programs for engineering education and research.”

They’re transcending something, that’s for sure.

My challenge for Jeff Thompson: Show up at an engineering class at your institution, read aloud the entire contents (i.e., the two paragraphs) of “Using Science to Minimize Sleep Deprivation that may reduce Train Accidents,” then engage the students in a discussion of what this says about “the current landscape for what it means to be a Carnegie R1 ‘Very High Research’ institution.”

Should be fun, no? Just remember, the best way to keep the students’ attention is to remind them that, yes, this will be covered on the final exam.

P.P.P.S. More here from Retraction Watch.

P.P.P.P.S. Still more here.

P.P.P.P.P.S. Retraction Watch found more plagiarism, this time on a report for the National Science Foundation.

Doctoral student and PostDoc positions in Finland

Several job opportunities in beautiful Finland!

Fully funded postdoc and doctoral student positions in various topics including Bayesian modeling, inference, and workflow, Gaussian processes, Bayesian neural networks, prior elicitation, probabilistic programming, Stan, etc. at Finnish Center for Artificial Intelligence, Aalto University, and University of Helsinki. I’m also one of the potential supervisors.

I can connect you with previous and current students and postdocs, so that you can ask their opinion on why they enjoy(ed) the group, and how it is like to live in Finland.

See more at fcai.fi/we-are-hiring

Blue Rose Research is hiring (yet again) !

Blue Rose Research has a few roles that we’re actively hiring for as we gear up to elect more Democrats in 2024, and advance progressive causes!

A bit about our work:

  • For the 2022 US election, we used engineering and statistics to advise major progressive organizations on directing hundreds of millions of dollars to the right ads and states.
  • We tested thousands of ads and talking points in the 2022 election cycle and partnered with orgs across the space to ensure that the most effective messages were deployed from the state legislative level all the way up to Senate and Gubernatorial races and spanning the issue advocacy space as well.
  • We were more accurate than public polling in identifying which races were close across the Senate, House, and Gubernatorial maps.
  • And we’ve built up a technical stack that enables us to continue to build on innovative machine learning, statistical, and engineering solutions.

Now as we are looking ahead to 2024, we are hiring for the following positions:

All positions are remote, with optional office time with the team in New York City.

Please don’t hesitate to reach out with any questions ([email protected]).

Postdoc on Bayesian methodological and applied work! To optimize patient care! Using Stan! In North Carolina!

Sam Berchuck writes:

I wanted to bring your attention to a postdoc opportunity in my group at Duke University in the Department of Biostatistics & Bioinformatics. The full job ad is here: https://forms.stat.ufl.edu/statistics-jobs/entry/10978/.

The postdoc will work on Bayesian methodological and applied work, with a focus on modeling complex longitudinal biomedical data (including electronic health records and mobile health data) to create data-driven approaches to optimize patient care among patients with chronic diseases. The position will be particularly interesting to people interested in applying Bayesian statistics in real-world big data settings. We are looking for people who have experience in Bayesian inference techniques, including Stan!

Interesting. In addition to the Stan thing, I’m interested in data-driven approaches to optimize patient care. This is an area where a Bayesian approach, or something like it, is absolutely necessary, as you typically just won’t have enough data to make firm conclusions about individual effects, so you have to keep track of uncertainty. Sounds like a wonderful opportunity.

Analyst positions available at the Consumer Financial Protection Bureau!

Jennifer Zhang, who took my applied statistics class a few years ago, writes:

I am now working at the Consumer Financial Protection Bureau in DC. I’m writing to share an exciting job opportunity that I hope some of your students would be interested in.

The Consumer Financial Protection Bureau (CFPB), a 21st century government agency that implements and enforces Federal consumer financial law and ensures that markets for consumer financial products are fair, transparent, and competitive, is recruiting this fall for the Director’s Financial Analyst (DFA) position to start in June 2024, and we want to encourage graduating seniors/recent graduates to apply.

Continue reading

PhD student, PostDoc, and Research software engineering positions

Several job opportunities in beautiful Finland!

  1. Fully funded postdoc and doctoral student positions in various topics including Bayesian modeling, probabilistic programming and workflows with me and other professors in Aalto University and University of Helsinki, funded by Finnish Center for Artificial Intelligence

    See more topics, how to apply, and job details like salary at fcai.fi/we-are-hiring

    You can also ask me for further details

  2. Permanent full time research software engineer position at Aalto University. Aalto Scientific Computing is a specialized type of research support, providing high-performance computing hardware, management, research support, teaching, and training. The team works with top researchers throughout the university. All the work is open-source by default and the team take an active part in worldwide projects.

    See more about tasks, qualifications, salary, etc in www.aalto.fi/en/open-positions/research-software-engineer

    This could be a great fit also for someone interested in probabilistic programming. I know some of the RSE group members, and they are great, and we’ve been very happy to get their help, e.g. in developing priorsense package.

A client tried to stiff me for $5000. I got my money, but should I do something?

This post is by Phil Price, not Andrew.

A few months ago I finished a small consulting contract — it would have been less than three weeks, if I worked on it full time — and I find it has given me some things to think about, concerning statistical modeling (no surprise there) but also ethics. There’s no particular reason anyone would be interested in hearing me ramble on about what was involved in the job itself, but I’m going to do that anyway for a few paragraphs. Maybe it will be of interest to others who are considering going into consulting. If you are here for the ethical question then you can skip the next several paragraphs; pick up the story at the line of XXXX, far below.

Continue reading

Faculty position in computation & politics at MIT

We have this tenure-track Assistant Professor position open at MIT. It is an unusual opportunity in being a shared position between the Department of Political Science and the College of Computing. (I say “unusual” compared with typical faculty lines, but by now MIT has hired faculty into several such shared positions.)

So we’re definitely inviting applications not just from social science PhDs, but also from, e.g., statisticians, mathematicians, and computer scientists:

We seek candidates whose research involves development and/or intensive use of computational and/or statistical methodologies, aimed at addressing substantive questions in political science.

Beyond advertising this specific position, perhaps this is an interesting example of the institutional forms that interdisciplinary hiring can take. Here the appointment would be in the Department of Political Science and then also within one of the relevant units of the College of Computing. And there are two search committees working together, one from the Department and one from the College. I am serving on the latter, which includes experts from all parts of the College.

[This post is by Dean Eckles.]

Blue Rose Research is hiring (again) !

Blue Rose Research has a few roles that we’re actively hiring for as we gear up to elect more Democrats in 2024, and advance progressive causes!

A bit about our work:

  • For the 2022 US election, we used engineering and statistics to advise major progressive organizations on directing hundreds of millions of dollars to the right ads and states.
  • We tested thousands of ads and talking points in the 2022 election cycle and partnered with orgs across the space to ensure that the most effective messages were deployed from the state legislative level all the way up to Senate and Gubernatorial races and spanning the issue advocacy space as well.
  • We were more accurate than public polling in identifying which races were close across the Senate, House, and Gubernatorial maps.
  • And we’ve built up a technical stack that enables us to continue to build on innovative machine learning, statistical, and engineering solutions.

Now as we are looking ahead to 2024, we are hiring for the following positions:

All positions are remote, with optional office time with the team in New York City.

Please don’t hesitate to reach out with any questions ([email protected]).

HIIT Research Fellow positions in Finland (up to 5 year contracts)

This job post is by Aki

The Helsinki Institute for Information Technology has some funding for Research Fellows and the research topics can include Bayes, probabilistic programming, ML, AI, etc

HIIT Research Fellow positions support the career development of excellent advanced researchers who already have some postdoctoral research experience. While HIIT Research Fellows have a designated supervisor at University of Helsinki or Aalto, they are expected to develop their own research agenda and to gain the skills necessary to lead their own research group in the future. HIIT Research Fellows should strengthen Helsinki’s ICT research community either through collaboration or by linking ICT research with another scientific discipline. In either case, excellence and potential for impact are the primary criteria for HIIT Research Fellow funding.

The contract period is up to five years in length.

I (Aki) am one of the potential supervisors, so you could benefit from my help (other professor are great, too), but as the text says you would be an independent researcher. This is an awesome opportunity to advance your career in a lovely and lively environment between Aalto University and University of Helsinki. I can provide further information about the research environment and working in Finland.

The deadline is August 13th 2023

See more at HIIT webpage

PhD or PostDoc position on simulation-based inference with Paul “brms” Bürkner

Hi all, this is Paul. Andrew was so kind to allow me to post a job ad here on his blog.

At the Technical University of Dortmund, Germany, I am currently looking for a PhD Student or PostDoc to work with me on simulation-based Bayesian inference research in the context of our BayesFlow framework.

BayesFlow is a Python library for efficient simulation-based Bayesian Inference. It enables users to create specialized neural networks for amortized Bayesian inference, which repays users with rapid statistical inference after a potentially longer simulation-based training phase. A cornerstone idea of amortized Bayesian inference is to employ generative neural networks for parameter estimation, model comparison, and model validation when working with intractable simulators whose behavior as a whole is too complex to be described analytically.

Both the BayesFlow library itself and its community are quickly growing. Our goal is to make it the gold-standard simulation-based inference library within the next couple of years.

For more details about the position, please see Paul Bürkner – Open Positions

I am looking forward to your applications!

Paul

Postdoctoral position at MIT: privacy, synthetic data, fairness & causal inference

I have appreciated Jessica’s recent coverage of differential privacy and related topics on this blog — especially as I’ve also started working in this general area.

So I thought I’d share this new postdoc position that Manish Raghavan and I have here at MIT where it is an important focus. Here’s some of the description of the broad project area, which this researcher would help shape:

This research program is working to understand and advance techniques for sharing and using data while limiting what is revealed about any individual or organization. We are particularly interested in how privacy-preserving technologies interface with recent developments in high-dimensional statistical machine learning (including foundation models), questions about fairness of downstream decisions, and with causal inference. Applications include some in government and public policy (e.g., related to US Census Bureau data products) and increasing use in multiple industries (e.g., tech companies, finance).

While many people with relevant expertise might be coming from CS, we’re also very happy to get interest from statisticians — who have a lot to add here!

This post is by Dean Eckles.

Messy data crashes into us

This short post is by Lizzie. 

Excellent job title alert! University of Nebraska-Lincoln has an open-rank position in messy data. Thanks to my former student, Dan, for sharing this.

In other news, I am in France (near the toy shop in this photo) where the radio also goes on strike. This means that at 8am last Thursday when I went to listen to the top-of-the-hour news I instead heard ‘There is a light and it never goes out, There is a light and it never goes out …’

Columbia is hiring a professor of political analytics

This came in the mail:

Columbia University is still accepting applications for a full-time faculty position at the rank of Associate Professor of Professional Practice or Professor of Professional Practice in Political Analytics. The Master of Science in Political Analytics program is the product of a partnership between the Department of Political Science and the School of Professional Studies at Columbia University. The inaugural student cohort will be welcomed this September 2023.

Interested candidates should apply to the link here by February 24th to receive full consideration.

Questions about the role or application process can be directed to Jamie Douglas, Senior Director of Faculty Recruitment, at [email protected].

I’m not directly involved in this program myself, but other political science faculty are involved. It sounds pretty cool. Maybe they’ll hire someone who does sports and business analytics too!

Blue Rose Research is hiring !

Blue Rose Research is looking to expand as we gear up to elect more Democrats in 2024, and advance progressive causes !

A bit about our work:

  • In the 2022 US elections, we used engineering and statistics to advise major progressive organizations on directing hundreds of millions of dollars to the right ads and states.

  • We tested thousands of ads and talking points in the 2022 election cycle and partnered with over a hundred organizations across the space to ensure that the most effective messages were deployed in hundreds of house, senate, gubernatorial, and state legislative races across the country – in addition we played a large role in helping issue advocacy groups and ballot measure campaigns ranging from reproductive rights to medicaid expansion.

  • We were more accurate than public aggregators in identifying which races were close across the Senate, House, and Gubernatorial maps.

  • And we’ve built up a technical stack that enables us to continue to build on innovative machine learning, statistical, and engineering solutions.

Now as we are looking ahead to 2024, we are hiring for the following positions:

All positions are remote, with optional office time with the team in New York City.

Please don’t hesitate to reach out with any questions ([email protected]).

Research fellow, postdoc, and doctoral student positions at Aalto University, Finland

We’re looking for research fellows, postdocs, and doctoral students for projects in

  • Bayesian workflows for iterative model building and networks of models (Proj. 7, Aalto University)
  • Evaluating and improving posterior inference for difficult posteriors
    (Proj. F9, FCAI/Aalto/Helsinki with Prof. Arto Klami)
  • Workflows for better priors (Proj. F19, FCAI/Aalto/Helsinki with Prof. Arto Klami)

See the abstracts below.

There are also many other topics in probabilistic modeling, ML, and AI at Aalto University and University of Helsinki

All topics and how to apply at

You can ask me (Aki) for more information

Aalto University and University Helsinki have strong Bayesian/ML/AI community. We contribute to open source software packages like Stan and ArviZ. Aalto pays postdocs well compared to many other countries. We have plenty of travel funds. Finland is a great place for living, with or without family. It is a safe, politically stable and well-organized society, where equality is highly valued and corruption is low. Extensive social security supports people in all situations of life. Occupational and national public healthcare in Finland are great and free. You can manage in work and everyday life well with English (no need to learn Finnish unless you want to). Finland has been ranked as the happiest country in the world in 2018–2021.

Topic: Bayesian workflows for iterative model building and networks of models

We formalize and develop theory and diagnostics for iterative Bayesian model building. The practical workflow recommendations and diagnostics guide the modeller through the appropriate steps to ensure safe iterative model building, or indicate when the modeler is likely to be in the danger zone.

Topic: Evaluating and improving posterior inference for difficult posteriors

Both MCMC and distributional approximations often struggle to handle complex posteriors, but we lack good tools for understanding how and why. We study diagnostics for identifying the nature of the computational difficulty, e.g. whether the difficulty is caused by narrow funnels or strong curvature. We also develop improved inference algorithms, e.g. via automated and semi-automated transformations.

Topic: Workflows for better priors

Bayesian models rely on prior distributions that encode knowledge about the problem, but specifying good priors is often difficult in practice. We are working on multiple fronts on making it easier, with contributions to e.g. prior elicitation, prior diagnostics, prior checking, and specification of priors in predictive spaces.

The cleantech job market: Every modeler is supposed to be a great Python programmer.

This post is by Phil Price, not Andrew.

I’ve had a run of luck ever since I left my staff scientist position at Lawrence Berkeley Laboratory to become a freelance consultant doing statistical modeling and forecasting, mostly related to electricity consumption and prices: just as I finished a contract, another one would fall into my lap. A lot of work came my way through my de facto partner Sam, but then my friend Clay brought me into a project, and every now and then my friend Aeneas has something that he needs for his company, and I had a couple of clients who found me through having heard about me without any personal connection.

One lesson is: even in today’s world, with LinkedIn and websites and blogs and other ways of making ourselves known to the world, personal contacts matter a lot in getting consulting work. Or at least that has been the case for me. That’s been good for me because I’ve had good contacts, but it’s not necessarily good for society. If you’re younger and don’t have a lot of work experience, and you don’t have many friends doing the same sort of work you’re doing, you won’t have the advantages I’ve had.

So, for seven years everything was great. But this year has not gone so perfectly: I’m down to two clients at the moment, and one of them only needs a little bit of work from me each month. I’m looking for work but, never having had to do it before, I don’t really know how. But one thing I know is that people use LinkedIn to look for jobs and for people to fill those jobs, so I updated my long-moribund LinkedIn profile and clicked a few buttons to indicate that I’m looking for work. Several recruiters have contacted me about specific jobs, and I’ve also been looking through the job listings, looking for either more consulting work or for a permanent job.

Three things really stand out. Here’s the TLDR version:
1. There’s a lot of demand for time series forecasting of electricity consumption and prices.
2. The modeler has to write the production code to implement the model.
3. It’s gotta be Python.

That’s pretty much it for factual content in this post, but then I have some thoughts about why one aspect of this doesn’t make much sense to me, so read on if this general topic is of interest to you.


I. Modeling and Forecasting of Electricity Supply, Demand, and Price.

There are quite a few jobs for electricity time series modeling, and for optimization based on that modeling. Some companies want to predict regional electricity demand and/or price and use this to decide when to do things like charge electric vehicles or operate water pumps or do other things that need to be done within a fairly narrow time window but not necessarily right now. And then there are other forecasting and optimization problems like whether to buy a giant battery to use when the electricity price is high, and if so how big, and how do you decide when to use it or recharge it. All of this stuff is right up my alley: I’m good at this and I have lots of relevant experience. To give an example of a job in this space, here’s something from a job description I just looked at (for a company called Geli): “Your primary responsibility will be to lead the development of our time series forecasting models for solar and energy consumption using machine learning techniques, but you will also help develop new forecasting models as various needs arise (eg: prototyping forecasting wholesale prices for a new market).” This is extremely similar to work I have been doing off and on for one of my clients for the past eighteen months or so. Sounds great.

And there’s a bullet list for that same job listing:
* Feature engineering
* Prototyping new algorithms
* Benchmarking performance across various load profiles
* Integrating new forecasting algorithms into our production code base with robust test coverage
* Collaborate with the rest of the team to assess how forecasts can be adjusted for various economic objectives.
* Proactively identify opportunities within [our company] that can benefit from data science analysis and present those findings.
* Work collaboratively in a diverse environment. We commit to reaching better decisions by respecting opinions and working through disagreements.
* Gain in depth experience in an exciting industry as you work with storage sizing, energy financial models, energy tariffs, storage controls & monitoring.

Continue reading

Hiring at Flatiron Institute (NYC): research scientists, postdoctoral fellows, interns, and software engineers at Flatiron Institute

Edit: Before going into detail, I would like to make it clear up front that I’m specifically looking for people with experience and a publication record in algorithms, open-source software, and directly relevant theory and methodology. Flatiron Institute as a whole is focused on the physical and biological sciences (not education, social science, finance, etc.).

Edit #2: I don’t know anything yet about the new Salary Transparency in Job Advertisements law and what that will mean for our job ads.

Hiring season is officially open! I’m now officially the group leader for computational statistics and am looking to hire at all levels.

Jobs

  • Postdoctoral Fellows: 2 year appointments with a 1-year extension baked in.
     
  • Open-rank Research Scientists: permanent appointments at all levels; we typically do not hire straight out of graduate school for these permanent positions.
     
  • Software engineers: permanent software engineering positions.
     
  • Summer interns: we bring in a large number of interns across Flatiron Institute and Simons Foundation, who are mentored by research scientists, postdocs, or software engineers.

Official job ads

Here’s the link to the official Flatiron Institute jobs board, where you will find the postdoctoral fellow and open-rank job ads:

Application dates

Flatiron Institute cafeteriaPostdoctoral Fellow applications are due 15 December 2022 for positions with flexible starting dates in 2023. We accept open-rank applications for permanent research scientist positions at any time, though we will also be hiring in the usual academic cycle (i.e., early 2023 interviews and job offers). We do not have an ad for software engineers up, but will create one if we find relevant candidates—we are always looking to hire permanent software engineers.

The official announcement for interns is not yet up on our jobs site, but I will post a separate blog entry when it’s up.

Please contact me directly

If you’re interested in one of these positions, please send me an email directly to discuss ([email protected]).

Center for Computational Mathematics Mission

This is the only place I’ve ever worked where the mission statement lines up so well with my own interests:

CCM’s mission is to create new mathematical approaches, algorithms and software to advance scientific research in multiple disciplines, often in collaboration with other Flatiron Centers.

The other centers have similar missions, because the institute was established to fill the gap in scientific funding for algorithms and software. If the mission appeals to you, you will probably like Flatiron Institute. More specifically, members of our center work on methodology, applications, and theory for computational stats and machine learning, as well as more traditional scientific computing in the form of optimization, differential equation solvers, non-uniform FFTs, phase retrieval, optimization etc.

We are all principal investigators in the sense that there are no top-down goals from the administration other than to work toward our mission. Our president, David Spergel, is an astrophysicist, which gives the whole place a more traditional academic feel than the current MBA-led situation in most universities.

Computational Statistics Group

Our group so far consists of

  • Bob Carpenter (Senior Research Scientist), working on computational statistics algorithms, Stan, and applied statistics (crowdsourcing, coherent diffraction imaging, genomics, etc.)
  • Robert Gower (Research Scientist), who’s a specialist in optimization and working with us and others on both variational inference and with me on optimization for large scale transcriptomics and biome modeling.
  • Brian Ward (Software Engineer), who’s been working on the Stan language, interfaces, and applications like CDI.
  • Yuling Yao (Postdoctoral Fellow), who’s working on Bayesian methodology, Bayesian inference and beyond, including some really exciting ML-motivated variational inference algorithms.
  • Charles Margossian (Postdoctoral Fellow), who’s working on massively parallel inference and convergence monitoring, adjoint methods for autodial of implicit functions (like root finders and differential equation solvers), as well as nested Laplace approximation.

Machine Learning Group

Flatiron Institute roof gardenThe complementary group to ours is machine learning, led by Lawrence Saul, and we’re hiring in machine learning as well as computational statistics (the line is admittedly blurry and purely administrative). Dave Blei is also visiting one day a week after being here for a year on sabbatical.

In addition to Dave, we have a steady stream of visitors. In our group, Justin Domke is visiting for 5 months in early 2023, and Edward Roulades (a Stan developer and applied mathematician/statistician), will be back to work on massively parallel inference next summer. Robert Gower also has a steady stream of optimization specialists visiting.

We also have a very active internship program and both postdocs and research scientists can recruit interns who we bring to NY and put up for the summer.

Focus on algorithms and computation

Although most of our permanent staff researchers and software engineers work on open-source software, we realize postdocs need to get a job, so we give them the flexibility to concentrate on research. We also understand that research is an international collaborative effort and we encourage postdocs and research scientists to maintain and develop academic collaborations outside of Flatiron Institute.

A highly collaborative environment

My favorite part of this place is that it’s packed to the rafters with scientists working on deep and interesting problems across the biological and physical sciences (our other centers are for computational astronomy, computational biology, computational neuroscience, and computational quantum physics).

christian mueller at blackboardI’m afraid we don’t do social science or humanities computing and are unlikely to hire anyone who’s concentrated mainly in these areas. The centers run popular science talks for each other on a weekly basis, which are really wonderful because they’re pitched at mathematically- and computationally-oriented scientists (so they assume you know basic physics and differential equations). We also do in-house training in computational statistics, machine learning, and applied mathematics—I often say it’s a great place to work for people who like math class (from both the teacher and student side). It’s been a wonderful place to learn new subjects and techniques.

Compute and support

Another great benefit of working here is our large-scale, state of the art compute clusters and the Scientific Computing Core staff who can help you get your C++, Fortran, or even Python code running efficiently on the cluster.

Like continental Europe and the old Bell Labs, we have a very pleasant lunch culture where we eat together almost every day (it’s not required but very pleasant; one of the pictures above is our cafeteria and another is the roof deck, where we have receptions after events and usually eat during the summer.

We also have truly fantastic admin support at all levels. I don’t think I could’ve imagined admin support this good and it makes a huge difference. Even our security guards are friendly and helpful.

We’re one of the few places that has sufficient meeting rooms for our staff size (as well as great professional AV support). We’re also one of those places with chalkboards and white boards in all the halls, and it feels very welcoming to be surrounded by mathematical scribbling (that’s my office you can see behind Christian Mueller writing on the blackboard below).

Simons Foundation

Flatiron Institute is part of the Simons Foundation, which is one of the largest non-governmental science funders. Jim and Marilyn Simons funded the foundation with a large enough endowment to exist in perpetuity. Flatiron Institute auditoriumSimons Foundation also runs all kinds of popular outreach programs around math and science education and engagement, including Quanta Magazine and Sandbox Films (science documentaries), Math for America, an oceanographic data collection arm, observatories, and a very large autism research insitiative dedicated to open-access data collection and curation. We even fund arXiv.

We are fully funded through the Simons Foundations and cannot apply for grants, though we are free to collaborate with whomever we want.

Offices and in-person work

We are not in the Flatiron Building, but have very nice digs in the Flatiron neighborhood of NYC (as you can see above), though hardly anyone has an individual office. Flatiron Institute and Simons Foundations have offices in two buildings at Fifth Avenue and 21st St, only a few blocks from Greenwich Village (NYU and subsidized postdoc housing) and Chelsea (Google and the Hudson River).

We’re 100% back to the office and do not hire people for remote positions.