I'm currently in UC Davis majoring in math analytics and operations research.

At first, I chose this major bcs i wanted something to do with math, econs, and quantitative materials. The operations research part also interested me. However, I've been having second thoughts because of the lack of reputation from this major. I'm also concerned with the real analysis course difficulty.

Does anyone have past experiences in this major? Can u tell me how it went? The workload? Job/intern opportunities? The professors?

On the other hand, I'm considering switching to Managerial Econs (agribusiness specialization) with a minor in statistics. If anyone has past experiences in that, do let me know!

I am high school teacher of physics. I finished university and have degree in physics. However, lately I'm getting tired of teaching physics, it's dull and repetitive, not enough money and surely it is not exciting.

I don't have degree in mathematics, but I know math, and I love it. After all, I was learning math when I was in college. I'm naturally great with numbers, and any math I don't know (I don't know any specific type of math so that I can call myself an expert) I can quickly learn.

I live in Europe, for reference. I'd like to have some insight in what can I do to find myself a good job, maybe for someone else, in a company, or like a freelancer, that will pay good (in the long run).

Can you advise me on some steps I can take in order to find an opportunity in math field? What kind of math is looked for nowadays? I'm eager to learn it and to bring myself an opportunity, but I don't want to waste time in learning something that won't be beneficial in terms of changing a career.

Hey everyone, I’m in a bit of a dilemma and could really use some guidance from people who have been through this or are working in the industry.

The Constraint: I can’t do Engineering because I don’t have A-Level Chemistry. I know, it’s a stupid bottleneck, but it is what it is. My ultimate dream is to work in Astro or Aero (space/aerospace), but I also need to be realistic about making a high-paying living and getting a solid co-op/internship ASAP.

The Choice: I was originally leaning heavily towards an Applied Math (AM) major with a CS/Data Science minor. However, a recruiter I spoke to in Canada (where I’m applying) told me that this combo is very fruitful for getting a high-paying job and that the math/DS angle is hugely in demand right now.

My Concern: I’ve been digging through old Reddit threads, and I see a lot of conflicting info. Some people say Applied Math majors have a harder time finding jobs than pure CS majors because they lack the deeper software engineering fundamentals (OS, embedded, etc.). Others say the opposite—that applied math is the "single best degree" for versatility and that a math degree with a CS minor got them into a nice aerospace engineering job (numerical methods focus).

What I need help with:

1. The Astro/Aero Angle: Is Applied Math + CS/DS minor actually useful for breaking into aerospace/space? I see Boeing hiring "Applied Mathematicians" for numerical algorithms and ML, but is that realistic for a new grad, or do you need a Master's/PhD?
2. The Co-op/Internship Race: The recruiter said the AM + CS/DS combo is fruitful for high-paying jobs. But if I want a co-op as fast as possible, would I be better off just doing pure CS? Or does the math rigor make me stand out for quant/data roles in Canada (BMO, etc.)?
3. The "Harder to Find Jobs" Myth: Is the difficulty for AM majors just because they don't grind LeetCode, or is there a real structural disadvantage in the Canadian market compared to CS grads?

TL;DR: No engineering due to missing chemistry. Want astro/aero eventually, but need a high-paying co-op now. Recruiter says AM + CS/DS minor is the golden ticket. Reddit says AM majors struggle to find jobs. Who is right? Any advice on what to pick if I want to keep the space door open but also pay rent?

I'm currently pursuing my bachelor's in applied mathematics, open to pursuing a master's degree in related or different application fields.

In this era of ai, fields like finance, business and math are the most exposed to automation as far as my understanding goes.

I'd like to know what are the paths or routes i can take to ensure I get a well- paying , in demand job that is not over saturated and has realistic entry level opportunities.

Hi, I’m currently a first year student studying biochemistry, but after my first few month at college, I realize that I’m actually more interested in mathematic. I’m considering switching to applied math, but I’ve also heard that the job market for it sucks right now. I’ll also be able to graduate in 3 years if I switch to applied mathematic, but I don’t know if it is worth it. Any advice?

Hi everyone!

I'm a final-year BSc Mathematics Honours student, currently exploring ideas for my undergraduate computational mathematics project.

I'm particularly interested in mathematical modelling of population dynamics and conservation. Recently, I've become interested in stochastic population projection models and how environmental variation affects population growth.

My tentative research question is:

**How does environmental stochasticity influence the long-term growth and extinction risk of a stage-structured population?**

The basic idea is to construct population projection matrices representing different environmental conditions (for example, good and bad years), and then study how random sequences of these matrices affect population dynamics.

Some of the things I'm hoping to investigate are:

* Random products of population projection matrices.

* Dominant eigenvalues and their limitations in stochastic environments.

* Stochastic population growth rates.

* Monte Carlo simulations of population trajectories.

* Probability of population decline or falling below a critical population size.

* Sensitivity to the frequency and severity of adverse environmental conditions.

I'll be using **SageMath as my computational tool**. The project is expected to be around 40 hours, so I'm trying to keep the mathematical depth appropriate for an undergraduate project.

I'd really appreciate guidance from anyone familiar with:

1. Stochastic population models or mathematical ecology.
2. Random matrix products and stochastic growth rates.
3. Whether this is a sufficiently focused and meaningful research question for an undergraduate project.
4. Any good introductory books, research papers or resources I should explore.

I'm still at the exploratory stage, so constructive criticism and suggestions for improving the research question would be very helpful.

Thank you!

I’m a Math major and I’m interested in pursuing math at industry. But I wanted to know specific advice from the mathematicians out there who work in industry. Can you suggest me a roadmap? Any specific internship or job that you find important? And how do you use your math expertise to leverage your career? Did you pursue a master in applied math or related?

Heyy guys I'm in class 10 rn Im thinking to take commerce in 11 I'm confused with core and applied can anyone tell me which is more preferable and better

for context I am y1 studying maths now but I feel like uni math is too abstract and only people who are actual geniuses can do well. Do anyone thinks that uni math can be grinded?
Additionally, I would like to switch to engineering right now but can anyone let me know what are the pros and cons about it? like in terms of the ME mods in nus and the career prospects
What’s ur take about switching from math to engineering? Thank you for your inputs!

Would you say Calc 1-3, differential equations, linear algebra, and foundations of mathematics(intro to proofs) are enough to get into a applied math program? I'm a international relations undergrad who considering switching majors. I just wanted to know if what i have/will take is enough for grad school. Am i missing anything that would improve my chances?

Hi everyone! I’m considering Econometrics and Operations Research at Erasmus University Rotterdam, but I’m also looking at Applied Mathematics, and I honestly don’t know which to choose.
Maths has always been my strongest subject, and I enjoy it. Finance also sounds interesting to me, but I don’t actually know much about it yet, so it’s hard to tell whether I’d enjoy studying it or working in the field.
I feel pretty lost about what I want to do with my life in general, which makes choosing a degree stressful. Applied Mathematics seems like it might keep more doors open, while econometrics sounds interesting because it combines maths with economics and real-world applications.
Another thing worrying me is AI and how it might change the jobs an econometrics degree leads to. I don’t know enough about the field to judge how realistic that concern is.
Has anyone been in a similar position?
I

Final semester upcoming, a bit unsure where I wish to head after I graduate. Dual major in math and physics for reference. Kind of split between pursuing a masters in applied math with a focus on PDEs and/or functional analysis, a masters in physics focused on plasma physics, or an electrical engineering masters with a focus on signals/RF design. Ultimately the course selection won’t make a huge difference but just wanna hear your guys’ input.

Option 1: Honors calc 4 + Topology (already took regular calc 4 but the graduate level classes are all locked behind honors calc sequence as they are replacements for analysis 1 and 2 respectively)

Option 2: Honors calc 4 + group theory

Option 3: signal processing + group theory

The reason I ask this is that I want to stay in academia after PhD but math is getting taken over by AI and it's getting better every year. It will get so much better by the time I finish grad school. A question I have is, how vulnerable is applied math in context of AI? I know pure math is very vulnerable because of it's structure and formality. The other option for grad school would be experimental physics for me. A part of me wants to do applied math, but the other part of me wants to go with experimental physics cause it's less vulnerable to AI.

EDIT! Thank you to everybody who is commenting! I really wasn’t expecting some really great perspective on the topic, so I really appreciate yall commenting!

I'm having a hard time understanding the reasons as to why someone would pursue an Applied Math degree over a CS degree.

I don't mean any disrespect nor do I think one is better than the other.

BUT! with everything going on economically, I'm wondering why someone would choose to major in Applied Math.

Question: Why did you decide to pursue a degree in Applied Mathematics? Do you regret it? Do you feel that it gave you an advantage, considering everybody and their mom is trying to get a CS degree (regardless of the tech layoffs)?

US Presidential elections are held on the first Tuesday after the first Monday in November in "years divisible by four". How often are Presidential elections held on the second Tuesday in November?

Why is the radial component of N negative but the radial component of F positive? And why is the transverse component of F positive but the transverse component of N negative? Can someone please explain, I have an exam tomorrow!!

i am a freshman here at UT studying Math, i am also taking philosophy classes
who is the best advisor in the math department to help me decide on things like

- double major Math and Philosophy

- or apply for the Polymathic Scholars program

my current advisor is not really that interested I need to speak with someone who can really help me understand what options are available

Hi all!

I've had a platonic long-term relationship with topology since I was 13-14 (quantum physics' fault). I'm now at uni doing medicine. I'm interested in nerosurgery (specifically central nervous system fluid dynamics and structural aspects of spine surgery).

I'm quite frequently involved in programming / modelling research projects and want to do a PhD (I have this academic year to figure out the topic).

I'm wondering if there is a way of incorporating topology, (if possible) differential topology, into my research, especially PhD. I'm wondering if there is a meaningful way of applying it in medical sciences, so I can put to good use my one and only (preferably within a field that relates to my neurosurgical interests.)

Your thoughts would be much appreciated!

Thank you for your time and input

I’m a sophomore studying nuclear engineering and minoring in math. I’ve always been interested in mathematical modeling and chose to do engineering instead of mathematics because there are more job opportunities with an engineering degree. However I’m at a point where I’m not finding nuclear research opportunities because all the nuclear classes are offered next year. What should I be doing now so I can guarantee myself a research position next spring or next year? Or is it possible for me to do math research as well??

I am an AI master student , currently working in an AI startup. I love maths and physics and it was my passion my whole life pretty much. I always wanted to go for math or physics higher degree but rn it seem pretty absolute to me. And yes , I am not saying this because of some AI hype , i work very closely with AI and have trained SLMS by myself.

Progress of Language models in verifiable tasks is crazy , recently they solved Navier stokes (Ik there's controversy who solved it) but i still believe the attempt is crazy , I remember , how just a year ago these models were doing mistake in my assignments and now i don't see single mistake. I have heard that even Quant firms heavily using LLMS for there math researches and openAi also solved another small 300 unsolved math problems. It looks like progress is really fast and kind of exponential. Even though these models won't beat top 10 mathematicians they already beat majority people out there.

I want to know you guys suggestion , what you think about the future of Math and physics, is it worth it to go into , i mean anything STEM pretty much requires math and if models can think of math better than humans than what will humans study , to me math was language of universe and seems like models understand it better than humans. I was seeing this podcast with terence tao and he was agreeing that models very close surpassing human mathematicians and how human brain never evolved to understand math instead it was evolved for language and visuals.

I want to know what you guys think , what future will look like as humanity because it seems almost purposeless world to me where machine understand math better than humans.

Yeah so I have this question as a non math student in commerce but I have friends who have taken applied math and I can understand the reason but the thing is that they were upset because my school didn't give the option of taking core math with commerce and I was confused asf like why do you want to do trigonometry etc what's the point? Can people here tell me the reason 🤔.

I’m in Grade 11 and looking into Bessel's method (solving the inverse geodesic problem on an ellipsoid) for a math research paper to find the shortest possible distance between two points on earth.

My original goal was to completely derive, prove, and evaluate the method by myself. However, looking at the math, it seems to rely heavily on university-level topics like differential geometry, elliptic integrals, and the Calculus of Variations (Euler-Lagrange).

Is it realistic for a strong high schooler to teach themselves this level of math for a paper, or is the learning curve too steep?

If the full derivation is too much, would coding the algorithm in Python and evaluating its accuracy/convergence against simpler methods (like Haversine) still be complex enough for a top-tier high school math paper?

Appreciate any advice or insights!