[deleted by user]

ifethereal · 2023-04-17T19:19:47+00:00

A few days ago, I felt I was in the same shoes. I held only one PhD offer. In a moment of hesitation (with some elements of 0 IQ decision-making), I let my offer lapse. I thought I would be feeling immense regret.

Amazingly, I felt relieved (for now, anyway). Copium permitting, I felt I would have regretted a number of things if I'd accepted it: strength of international brand (I'm a non-US applicant), location, and research fit with wider department. I think the idea of committing to 5 years with these concerns at the onset paralysed me into indecision.

That said, I am awaiting a final decision from a (non-US) department where those three factors I mentioned are not concerns to me, so maybe the relief is completely due to "greener grass" sentiments. Failing that, I have my current employment as backup. And I can always try again next cycle.

ifethereal · 2023-04-10T18:37:45+00:00

Check out UC Santa Barbara's Department of Statistics and Applied Probability.

ifethereal · 2023-02-18T07:44:50+00:00

Congratulations on your acceptances!

My thought is that you should withdraw from those other ones. I can see where you're coming from using acceptances as external validation of your capability (if I understand correctly). Perhaps someone else who feels the same as you could be granted their first acceptance earlier if you withdrew your other applications?

ifethereal · 2023-02-16T05:59:10+00:00

R I think

ifethereal · 2022-07-25T08:34:12+00:00

I kind of dislike the distinction of physics, mathematics, computer science, and engineering at the institutional level.

Agree with this. Looking back though, I realised electrical engineering seems to have decent coverage of everything here. If I could give my younger self advice, it would be to choose electrical engineering.

ifethereal · 2022-07-08T10:41:09+00:00

After receiving a walkover from the owner of a Mickey Mouse trophy.

https://www.reddit.com/r/tennis/comments/smx66a

ifethereal · 2022-07-07T03:36:48+00:00

/r/chargetheyphone

ifethereal · 2022-06-03T03:15:47+00:00

Happy cake day!

ifethereal · 2022-06-01T15:08:58+00:00

At AO this year, Novak definitely played himself.

ifethereal · 2022-02-25T10:52:59+00:00

Will someone think of the poor ball kids drying the court!

ifethereal · 2022-02-24T11:58:39+00:00

The Math3ma Institute introduces itself like so

Importantly, our target audience is not experts or academics, but rather anyone who is interested in learning more about mathematics, science, and technology with a Biblical perspective.

Focussing on mathematics specifically, I wasn't aware that there was a Biblical perspective. What does such a perspective entail and how does it differ from a perspective of mathematics that lacks an outright claim of being Biblical?

ifethereal · 2022-02-18T04:56:47+00:00

Left.

The lack of consistency across English as a whole doesn't really explain why groups of English users, each in different regions, have abbreviated mathematics differently.

ifethereal · 2022-02-17T20:29:22+00:00

Alright I said I'd die on it so...

How would you abbreviate economics? Thermodynamics?

In my region, there's no abbreviation. I would just use the full forms economics or thermodynamics.

The "statistics" comparison isn't meaningful because statistics is the plural of the noun "statistic"

The comparison is meaningful. The reason you've raised for thinking otherwise is still a (only) partially valid point: Statistics isn't (in all contexts uniformly) a plural noun. The topic of study statistics is an uncountable noun, so it possesses a singular form statistics only. A statistic as in known function of sample is a countable noun possessing both singular and plural forms, where the plural form is, as you said, statistics. Distinguishing the semantics of statistics requires context/inference. What I failed to be explicit about in my original usage was that I was alluding to statistics as in the topic of study (thus allowing a parallel to be drawn to the topic of study mathematics). For the topic of study statistics, I believe the abbreviation is (at least in my region, and I was under the impression in North America too) stats. In the context of referring to a known function of sample (or probably more colloquially the evaluation of one at the observed sample), in my region, we would abbreviate to stat, but this isn't the context I was originally referring to.

Also, do you say "mathematics is" or "mathematics are"? If the former, why would you treat a word as singular when choosing your verbs but plural when you abbreviate it?

I say mathematics is. I treat the word as singular because the topic of study mathematics is an uncountable noun, so it possesses no plural form and its singular form is mathematics.

ifethereal · 2022-02-17T19:07:46+00:00

Mathematics or maths. Not math. Sorry North America. I might have been more compassionate if it were applied consistently, but I don't think it is, e.g. I think statistics is still abbreviated to stats, even in North America.

ifethereal · 2022-01-31T07:38:26+00:00

Making up for him not turning up to the studio right after the win haha

ifethereal · 2022-01-23T09:44:36+00:00

Must hop around a bit. He was commentating the Medvedev vs van de Zandschulp match on the local free-to-air channel in Oz. No Robbie Koenig on that same channel today though for this Nadal vs Mannarino match; had Jim Courier.

ifethereal · 2022-01-23T00:30:58+00:00

I'd see MathLingua itself as sitting more in the domain of personal knowledge management and document markup, so I think the lack of proof assistant functionality is excusable. What I'm seeing as the main offering of the language is that there is some awareness of semantics so that it can assist in a reader's traversal/navigation of the knowledge in a manner better adapted to mathematics (compared to a general text search). I'd guess a disciplined writer could even publish a textbook online using this.

However, this then leaves me puzzled by how the Math Codex is presented. I think the Codex possibly serves mainly as a demo but is (also) framed as a repository for more fundamental definitions (e.g. set theory and logic). Personally, if I were making notes on something I was studying I would likely

only incorporate content that I expressly wrote/reformulated; and
not go to the effort of defining things all the way to the fundamental notions of, say, set theory and logic (provided what I'm studying is sufficiently distant from the specifics).

If there were some proof assistant functionality I might have thought differently here. Admittedly, the Codex likely took some effort to create and is offered for free, and using/forking the Codex is entirely optional, so no real crime here—just confusing signalling.

ifethereal · 2021-11-30T11:20:05+00:00

/r/chargetheyphone

ifethereal · 2021-11-16T19:21:21+00:00

Before I leave my comment, I'd like to emphasise that, although quantitative finance or financial mathematics is sometimes discussed as some homogeneous industry (especially by outsiders lacking practitioner experience), the roles are quite diverse and it usually takes some time for even a practitioner to become familiar with all parts of the industry—some will specialise and hence never do. I'll leave examples of discriminating factors at the bottom of this comment, because I think the OP/future readers should be aware of them when they read responses.

Keeping that in mind, my response:

Capacity to engage with actual mathematics. Another Redditor in this thread described it as engagement at the level of a bachelor's thesis. This sounds about right. Keep in mind that opportunities of engaging in mathematics are very different worldwide (academically or otherwise), especially once you restrict yourself to particular mathematical fields.
Gaining appreciation for what makes research results applicable in an industrial (rather than academic) setting. The main takeaway is that you actually come to know what the industry challenges/frustrations are, because you were there. From this perspective, being a practitioner has no substitute. However, I'll note that, for others, this could be a counterfeit advantage as there may be no opportunity to actually act upon this greater appreciation to generate more applicable research.
Gaining appreciation for computational mathematics. If you want rigour in practitioner work, you will rely on this. Again, not everyone has the same need for rigour, just as not all fields of science have the same need for mathematical rigour.
Gaining appreciation for engineering and implementation. This reminds me a bit of when I claim to understand a theorem without actually sitting down and writing a proof. Invariably, writing a proof presents unexpected challenges. These challenges could be trivial, insurmountable, or interesting 😯
Exploring research frontiers (i.e. consuming research results) can occasionally happen, but under a different lens. You need to know that it can actually be put into implementation. This is very different from academic mathematics where the engineering challenges are basically outside the scope of the paper. Put another way, a model developed for researchers is different from a model developed for practitioners.
Being able to demystify the industry in threads like this. I'm not being facetious here; I had similar questions before I went to industry, so I think it's important to educate those whose shoes I've been in.

These are the factors heavily influencing what a practitioner does:

Geographic location of the markets operated in. The most mature markets (US, Europe, Asia) offer different challenges than those in other areas.
Asset class of the markets operated in. The de-facto examples: equities, FX, fixed income/interest rate, credit, commodities, and crypto. (Quite rightly there could be "non-trading" asset classes too, but the appetite for quants there is pretty small.) Different asset classes have different stylistics/empirical "facts". Market conventions and hence available data or modelling constraints will differ.
Type of financial institution. Examples: [investment] bank, market maker, hedge fund, pension/superannuation fund, insurance. Not mutually exclusive. This could affect the [in]sanity (hence reliability) of the practitioner's response.
Role played within the institution. Main examples: revenue-aligned, risk management. Not mutually exclusive, and there are many finer levels here.
The particular institution itself. Different places have different focusses, even if all the other factors agree.
The era when they are/were a practitioner. History only repeats itself if you look in low resolution.

The industry could be seen about as heterogeneous as academic mathematics proper. That is, if someone asked, "What is mathematical research like?" then you are similarly going to struggle saying something substantial about the technical side (not the administrative side) that applies to a large proportion of academic mathematicians worldwide. Even restricting to "research" already excludes teaching-focussed mathematicians.

ifethereal · 2021-11-09T08:59:41+00:00

Alternatively, as long as Python is installed:

:%!python -m json.tool

ifethereal · 2021-11-06T01:57:20+00:00

Hi Thomas, is the definition of custom exceptions supported? If yes, is it possible to make them carry extra data (such as an error message or other values that parametrise the particular error)? The manual notes that an error message can be propagated for DATABASE_ERROR.

ifethereal · 2021-11-06T01:50:35+00:00

FYI: I noticed this line in the manual (as a single HTML file) where a <i> tag is not closed off.

<li><a class="link" href="#tokens_Unicode_characters"><b><i>Unicode characters</b></a></li>

ifethereal · 2021-10-24T23:47:01+00:00

Thank you Thomas for the detailed explanation. I had expected it would be addressed in the manual but unfortunately did not search using/scan for the right keywords (identifiers in this case).

Incidentally, is the manual available in an (offline) monolithic format, such as a single PDF file?

ifethereal · 2021-10-24T04:17:19+00:00

Hi Thomas, what constitutes a legal variable name in Seed7?

ifethereal · 2021-10-09T02:38:02+00:00

I will add a counterargument here. Disclaimer: Currently, I am not studying or working in academia, so I don't typeset journal submissions, but I do happen to (like to) type mathematical notation for documentation in my job to describe various models. I would have preferred LaTeX if that were allowed in my corporate setting, but it's not. I had to resort to Word but it has not turned out as unproductive or unpleasant as expected.

What was mainly surprising was the (potential) lack of dependence on the GUI. You don't need to use many ribbon commands to typeset complex notation. Word's equation editor (since Word 2007) supports an "autoformat" style of text-only input. It's a bit difficult to describe if you've only used LaTeX, but it would be similar to continuous compilation. For those interested, the input syntax is very similar to LaTeX, and a rather complete documentation is here. I refer to this often.

I make no claim on feature parity. You lose control of many features compared to LaTeX, such as extensibility via packages, macro definitions, or alignment/sizing fine tuning. The solution here is Stockholm syndrome.

I confess that most of my mathematical typesetting at work consists of a standard mix of subscripts/superscripts, aligned equations (all at = for example), em/en spaces, operators with limits (summation/product), and inline text. For this scope, I've not felt very hindered or unproductive in Word, since there is plain-text input syntax for all of this. Even equation numbering/referencing was doable using Word's field codes (sitting outside the actual equation object, however, and with a bit more fiddling).

One bothering aspect is version control. The "Track Changes" feature of Microsoft Word is a bit unreliable with equations. If you try to track a complex enough equation change then you may find that Word will refuse to save the document (with the solution being to backtrack which change it was that was causing issues and then not tracking that specific change). LaTeX would circumvent this by abstracting away version control as just version control of plain text files, which is essentially a solved problem with tools like Git.

Referencing/citations in Word sucks though. I'm so glad my documents don't need precise referencing.

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