Still Struggling finding a data science job

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  • #1
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Hello,

After more than 18 months of applying for jobs in my field (Ph.D. in Electrical Engineering/Wireless Communication) and in others (e.g., Data Science), in my country of origin, the country of graduation and residency (Canada), and other countries, I still haven't been called for any technical interview. I don't have experience, but I think I have some qualifications that I can build upon. So, the question is why I am not being considered?

I feel that the Data Science field is very competitive, because it seems that all people try to get in because of the hype around it, and I have little to no chance there in this wave, although I have been developing some related skills in Python and did some personal projects. Also, in my experience people are not willing to connect with me, maybe because I don't have much to offer in that area. One senior data scientist was nice enough to meet with me to edit my resume to look appealing for data science positions, but that was about it.

Currently, I am holding a short-term research position, but it will end in few months. I need to do something to land a job. I am thinking to get some certificate that may help me. I am thinking of three options:

1- Getting a master degree in computer science.
2- Getting a certificate in data science from a continuing education program from a local university.
3- Getting a certificate in networking, like CCNA.

Which one is better? I care about how much time it takes, and how much money it costs, but I also care if it will pay off when I finish.

What do you think? If you have any other suggestion, I am all ears.

Thanks in advance
 
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  • #2
Stephen Tashi
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1- Getting a master degree in computer science.
2- Getting a certificate in data science from a continuing education program from a local university.
3- Getting a certificate in networking, like CCNA.

Which one is better?
In your search for jobs, did you see job descriptions that wanted 1,2, or 3 ?
 
  • #3
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In your search for jobs, did you see job descriptions that wanted 1,2, or 3 ?
I saw some descriptions that want 1 and 3, but for 2 they ask about the skills taught during the program, not the certificate itself.
 
  • #4
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Of the three, I think #2 is the least likely to result in a job, as those types of certificates aren't highly regarded*. The experience they gave you could be beneficial, but frankly you should be able to look through the curriculum and pull those ideas out for yourself.

In general, the demand for people with a deep understanding of statistics and machine learning, combined with some programming skills, is extremely high. The demand for people who learned a little pandas and used a few sci-kit learn classes is extremely low. The question is - are you the first being misconstrued as the second? Or are you closer to the second? If it's the first, then you need to fix your resume (more, or again). If it's the second, then either you need to really amp up your personal projects, or you need a masters/phd in stats with a focus in machine learning.


The networking bit is really different. I'm not sure what your motivation is to go that route, but unless it's something you've been working with in your spare time, it seems pretty strange. After all, there are a lot of technical certifications out there - so why that one? Have you consider any AWS certs? Have you looked at IT jobs? In general, life in IT seems like hell, so it's not my first suggestion, but it's a lot better than unemployment, and could lead to other good places.

*"Least likely" doesn't mean zero! So if it's free, why not?
 
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  • #5
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The second option is not free. I didn't know there is a certificate in AWS. How is this better than say CCNA?Is it more in demand? Will I find a better job once I finish it?

I have deep enough understanding of statistics and some programming skills. But the problem I think is that my statistical background is encapsulated within another field than statistics, and maybe recruiters don't believe me when I say in my resume that I know statistics, with a degree in Electrical Engineering (as an example, someone told me to find a job in electrical companies!!).

The networking bit is to go around HR recruiters who might have been filtering out my resume based on a list of words they search for, and overlooking the potentiality part.

What example are there for IT jobs?
 
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  • #6
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The second option is not free. I didn't know there is a certificate in AWS.
There are at least ten! [edit: make that eight, I double counted!]

How is this better than say CCNA?Is it more in demand? Will I find a better job once I finish it?
It's not better, that's a complicated word. But devops definitely fits more with a statistics/programming/data science background. The statistical modeling is often (usually!) the smallest part of the solution. Social processes such as presenting the solution, getting buy in from customers, etc. are a big part. But AWS knowledge would help with another major component: Preparing the data sources, creating the environment you'll be working in, and deploying the solution. That's a lot of important work right there.


I have no idea whether you'll find a better job or not. I just think it makes more sense. Hopefully others will give their opinions as well, as you should get some variety in voices before deciding.
 
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  • #7
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Is the AWS certificate well-recognized in the industry like CCNA? I mean which is likely to land me a better job without experience, and almost immediately after I finish? I am broadening my options to other areas other than data science. Data science seems interesting and all, and I am familiar with its steps and procedures, theoretically and technically, but if I cannot get a job in data science, then it is no good for me. As I said, the hype around machine learning and data science makes it very competitive.
 
  • #8
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You need to reconsider what's going on here: you have a PhD in electrical engineering and you're looking to get associate level certs. Something is obviously very wrong with your situation, I don't know what it is.
 
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  • #9
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I think Qurks probably said what I've been thinking.

I mean, I'm trying to be helpful. But honestly, whatever is keeping you from being employed, I'd be really surprised if a CCNA (or AWS cert) will fix it by itself.

There's something else going on that we don't have access to, and I worry nothing we say will really get to the root of the problem.
 
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  • #10
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This is what I want to know. There is something very wrong, but I don't know what it is!! I am not getting positive responses (have never reached technical interviews. All I got was 3 phone interviews since Mid 2016), for the hundreds of applications I have submitted in different areas!! I don't think I am not that unqualified to do anything. How can I know what is going on? I update my resume all the time, and I doubt it is the main problem. Networking might be a problem for me, though. But is this the main reason I haven't gotten responses for my applications? I don't know.
 
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  • #11
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I would skip the idea of pursuing anything related to data science for two reasons:
1) Your education and experience is not related to that field.
2) You are not able to express a compelling reason why you would want to enter that field. "Hype" is a terrible reason to enter that field.

How does a potential employer know that you are going to stick with data science once they hire you? You are not giving them any reasons to believe you will become a good data scientist, or that you can stick with it. Maybe you try it, and find you don't like it after all, and lose motivation and quit after a few months. That's a huge risk for an employer. They already see that you are switching from studying EE to data science, so that confirms their belief that you might not stay in the field.

Your interests seem to be all over the place (data science, IT, statistics, programming). Try to focus on areas where you already have some experience, like your existing research position. There is a huge demand for people in the Wireless field (at least in the USA), so I am surprised you are not getting any interest there.
 
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  • #12
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I would skip the idea of pursuing anything related to data science for two reasons:
1) Your education and experience is not related to that field.
2) You are not able to express a compelling reason why you would want to enter that field. "Hype" is a terrible reason to enter that field.

How does a potential employer know that you are going to stick with data science once they hire you? You are not giving them any reasons to believe you will become a good data scientist, or that you can stick with it. Maybe you try it, and find you don't like it after all, and lose motivation and quit after a few months. That's a huge risk for an employer. They already see that you are switching from studying EE to data science, so that confirms their belief that you might not stay in the field.

Your interests seem to be all over the place (data science, IT, statistics, programming). Try to focus on areas where you already have some experience, like your existing research position. There is a huge demand for people in the Wireless field (at least in the USA), so I am surprised you are not getting any interest there.
I didn't say "hype" is the reason that I am entering data science. I rather said that the "hype around it" makes it very competitive and difficult to get in. There is a difference. I don't put "hype" as a reason to become a data scientist in my resume, and that I am interested in pursuing this path. I put courses and projects to express my interest.

I think my background (especially in statistics) fits better for data science than any other field (beside wireless communication).

People from different backgrounds such as business, biomedical engineering, and physics switch to the the field of data science, why switching from EE is perceived worse than from other fields in your view?!

Well, in Canada the wireless field is not as in the US, and I have limitations moving to the US (I need to apply from outside, which by itself reduces my chances a lot to find a sponsor to have a work permit or its equivalent in the US, ... etc).

I am interested in data science over other options. I listed the others because I am trying to find a solution to my situation, as data science hasn't worked out for me so far. The research positions are temporary.
 
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  • #13
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I agree with what the others said- it's weird that you can't even get an interview with what I would think is a strong credential (PhD in EE/wireless communications). Getting a cert in data science or networking aren't *bad* options, but it's not like you can just wave one of those certs in front of an employer and instantly get a job offer, if that's what you're hoping for. They still have that old, annoying problem- can't get a job without experience, can't get experience without a job.

My suspicion is that something is wrong with your job hunting process. What did other people from your PhD program do for jobs? If they got jobs and you can't, that tells you something. It might be as simple as just writing your resume in a bad way. You could try showing it to a professional service, or just ask anyone you know who works in the field to take a look at it. One possible problem is that if your resume looks too "academic," employers won't know what to make of it.

Have you been applying to US jobs too? (or any other country, for that matter). Needing a sponsor does hurt, but it's not impossible.
 
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  • #14
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I agree with what the others said- it's weird that you can't even get an interview with what I would think is a strong credential (PhD in EE/wireless communications). Getting a cert in data science or networking aren't *bad* options, but it's not like you can just wave one of those certs in front of an employer and instantly get a job offer, if that's what you're hoping for. They still have that old, annoying problem- can't get a job without experience, can't get experience without a job.

My suspicion is that something is wrong with your job hunting process. What did other people from your PhD program do for jobs? If they got jobs and you can't, that tells you something. It might be as simple as just writing your resume in a bad way. You could try showing it to a professional service, or just ask anyone you know who works in the field to take a look at it. One possible problem is that if your resume looks too "academic," employers won't know what to make of it.

Have you been applying to US jobs too? (or any other country, for that matter). Needing a sponsor does hurt, but it's not impossible.
Thank you. I had my resume critiqued by a senior data scientist. He said he thinks I know data science from my field, but I don't know how. I edited my resume accordingly, but still not getting responses (to be completely honest, I got one phone interview after I edited it, but not sure if it was a coincidence, or because I edited it, because I applied to tens of positions after editing it, and the responses were negative if there was a response at all).

Some of the people I know are from the same department, but not necessarily in my field. One with a PhD in cloud computing, and got hired in a big company immediately. Another in image processing and computer vision, and I think his previous experience in coding has helped him get a position. The people I know in my field are still doing their postdoc. But I don't know anyone from my field in the industry.

Actually, no. I haven't tried in the US, because I imagine it would be very difficult and constraining to have a sponsor.

The senior data scientist was super nice to reply me and accept to meet me (actually he is the one who suggested to meet in person), but my experience in reaching out to have a feedback about my resume hasn't been positive. People accept your invitation to add them to your connections on LinkedIn, but they then don't reply your messages!!
 
  • #15
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Thank you. I had my resume critiqued by a senior data scientist. He said he thinks I know data science from my field, but I don't know how. I edited my resume accordingly, but still not getting responses (to be completely honest, I got one phone interview after I edited it, but not sure if it was a coincidence, or because I edited it, because I applied to tens of positions after editing it, and the responses were negative if there was a response at all).

Some of the people I know are from the same department, but not necessarily in my field. One with a PhD in cloud computing, and got hired in a big company immediately. Another in image processing and computer vision, and I think his previous experience in coding has helped him get a position. The people I know in my field are still doing their postdoc. But I don't know anyone from my field in the industry.

Actually, no. I haven't tried in the US, because I imagine it would be very difficult and constraining to have a sponsor.

The senior data scientist was super nice to reply me and accept to meet me (actually he is the one who suggested to meet in person), but my experience in reaching out to have a feedback about my resume hasn't been positive. People accept your invitation to add them to your connections on LinkedIn, but they then don't reply your messages!!
Wait a second. Data science isn't your field- it's a pretty different field. Do you know anyone who works in *electrical engineering* who could look at it?

Those people you mention from your department also sound different. cloud computing, image processing, computer vision are all more on the software/programming side. Admittedly I don't know anything about Wireless Communications, but I would have thought that would be more on the hardwire side. (Maybe I'm wrong about that? But if I'm wrong, a lot of employers might be wrong too. Something to make clear in a cover letter/resume).

You could ask your professors to connect you with previous students from your field who got jobs, or at least tell you where they got jobs. About LinkedIn- see my response in the other thread, but agreeing to a connection there barely means anything. It's easy to click yes, much harder to actually write a message or give any useful help. Still, at least you can see what kind of jobs people got.

I would think it's worth applying for jobs in the US too, assuming you're willing to move.
 
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  • #16
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For me, it is more in the theoretical side, not hardware. We propose system models, analyze them mathematically, and finally do simulations. People in RF engineering work more on hardware design for the antennas (they are in demand more than us). I think the title Electrical and Computer Engineering is part of the problem. People may not know how many specializations there are under than name, and it is not only about power generation, or circuit design.

I will consider applying in the US if things don't go well in the coming few months. I am willing to move if I could secure a job there.

....You could ask your professors to connect you with previous students from your field who got jobs, or at least tell you where they got jobs......
Good point. I think asking my PhD supervisor about his previous students is the best way to connect. I will try that.

Thanks
 
  • #17
StatGuy2000
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I would skip the idea of pursuing anything related to data science for two reasons:
1) Your education and experience is not related to that field.
2) You are not able to express a compelling reason why you would want to enter that field. "Hype" is a terrible reason to enter that field.

How does a potential employer know that you are going to stick with data science once they hire you? You are not giving them any reasons to believe you will become a good data scientist, or that you can stick with it. Maybe you try it, and find you don't like it after all, and lose motivation and quit after a few months. That's a huge risk for an employer. They already see that you are switching from studying EE to data science, so that confirms their belief that you might not stay in the field.

Your interests seem to be all over the place (data science, IT, statistics, programming). Try to focus on areas where you already have some experience, like your existing research position. There is a huge demand for people in the Wireless field (at least in the USA), so I am surprised you are not getting any interest there.
The situation in Canada is very different from the US in this regard -- only a handful of companies dominate the telecommunications market (Rogers, Bell, and Telus being the big 3), thus limiting the number of positions open for wireless communications. Furthermore, there is little research in wireless communications outside of academia in Canada (unlike in the US).

Data science, on the other hand, is a growing field in Canada (particularly in larger cities like Toronto and Montreal), so I can see why @EngWiPy would focus in those areas.
 
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  • #18
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Data science, on the other hand, is a growing field in Canada (particularly in larger cities like Toronto and Montreal), so I can see why @EngWiPy would focus in those areas.
The problem is, it's also a field that lots and lots of other people are trying to get into. You've got competition from experienced programmers, statisticians, and data analysts all trying to get a piece of the pie, not to mention people that actually got specialized degrees focused on ML and/or data science. Like Locrian said, what they really want are people who experts in statistics, programming, *and* ML, not just one of those fields with a smattering of the others. The usual advice I've seen is to spend a long time both learning the field and also building up an impressive portfolio of personal projects.
 
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  • #19
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"Data science" degree I think is a euphemism for a watered down statistics degree with a programming course and an applied ML course. I'm actually a bit curious why programming is considered so important for ML since ML is usually orthogonal to most typical programming. Also most stats people don't do ML, at least where I am.

I actually would say the most technically rigorous is probably in the EE department, the CS machine learning students I have seen are kind of incompetent and bad at math.
 
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  • #20
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People from different backgrounds such as business, biomedical engineering, and physics switch to the the field of data science, why switching from EE is perceived worse than from other fields in your view?!
Switching from EE to data science is not worse than switching from those other backgrounds. But just because those other people switched doesn't mean that you will be able to do the same just as easily. Maybe they caught a lucky break, or they had some prior work experience in the field, or people already working in the industry told them about an unadvertised position at their company. Maybe they were like this guy who did a lot of open source work in the field, after switching from pursuing a degree in biology.

You have to look at this from an employer's perspective. Why would they hire you for a data science position over somebody else? They are probably getting hundreds of resumes for a single position. The other applicants might already have work experience in the field, they might have taken a greater number of relevant courses than you, and they may have completed independent data science projects/papers which are out on the web for employers to look at (e.g. github.com or similar web sites), and they may have taken MOOCs and have had some track record there (e.g. perhaps something like this). Ask yourself, what can I do to compete against those people?

I think you ought to figure out what your strengths are, what you enjoy doing, and what prior experience you bring to the table, and devote all of your energies towards pursuing employment in that particular field. It may be data science, it may be something else. But jumping around to a lot of different fields is not going to work, IMO.
 
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  • #21
StatGuy2000
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The problem is, it's also a field that lots and lots of other people are trying to get into. You've got competition from experienced programmers, statisticians, and data analysts all trying to get a piece of the pie, not to mention people that actually got specialized degrees focused on ML and/or data science. Like Locrian said, what they really want are people who experts in statistics, programming, *and* ML, not just one of those fields with a smattering of the others. The usual advice I've seen is to spend a long time both learning the field and also building up an impressive portfolio of personal projects.
The thing is, when it comes to many STEM fields, virtually all positions in Canada have lots of other people trying to get into them. So this isn't especially unique to data science. The OP is trying to determine what he can do to increase the probability that he can land a position outside academia.

I have already explained why wireless communication is (if not a dead end), very difficult to break into in Canada. So why not try to have him pursue where jobs are actually advertised (even if there is competition)?
 
  • #22
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Switching from EE to data science is not worse than switching from those other backgrounds. But just because those other people switched doesn't mean that you will be able to do the same just as easily. Maybe they caught a lucky break, or they had some prior work experience in the field, or people already working in the industry told them about an unadvertised position at their company. Maybe they were like this guy who did a lot of open source work in the field, after switching from pursuing a degree in biology.

You have to look at this from an employer's perspective. Why would they hire you for a data science position over somebody else? They are probably getting hundreds of resumes for a single position. The other applicants might already have work experience in the field, they might have taken a greater number of relevant courses than you, and they may have completed independent data science projects/papers which are out on the web for employers to look at (e.g. github.com or similar web sites), and they may have taken MOOCs and have had some track record there (e.g. perhaps something like this). Ask yourself, what can I do to compete against those people?

I think you ought to figure out what your strengths are, what you enjoy doing, and what prior experience you bring to the table, and devote all of your energies towards pursuing employment in that particular field. It may be data science, it may be something else. But jumping around to a lot of different fields is not going to work, IMO.
As far as I know, there is no major in data science, and data scientists come from a variety of backgrounds. The rest of your post makes more sense; I need to compete with others and show what I can do that makes me stand relative to others. But still, I think not being considered at all (even for junior positions) with my background, signals something else going on, and I am not sure what it is.
 
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  • #23
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The situation in Canada is very different from the US in this regard -- only a handful of companies dominate the telecommunications market (Rogers, Bell, and Telus being the big 3), thus limiting the number of positions open for wireless communications. Furthermore, there is little research in wireless communications outside of academia in Canada (unlike in the US).
Why restrict the job search to telco companies in Canada? (The situation with respect to telco companies is the same in the USA).

Surely there must be some semiconductor companies (ex: Intel), equipment manufacturers (ex: Ericsson), government agencies, and consulting firms that could use the skills and experience of the OP in the wireless field, even if it tends more to the theoretical side. Figure out what practical skills you have or can learn reasonably well, find companies that need those skills, and go apply for open positions at those companies. Try to find people inside those companies who can refer you to open positions (they often get bonuses for finding candidates).

When I was a graduate student and looking for a job, my chosen field was largely theoretical in nature (queuing theory), but I had some related practical knowledge in C programming, simulation, performance evaluation, and computer architecture which I was able to use to land a position in industry.
 
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  • #24
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Most jobs in the US related to communications require security clearance, so citizenship. At least that's nearly all of the jobs related to communications/signal processing in the US when searched*.
 
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  • #25
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The thing is, when it comes to many STEM fields, virtually all positions in Canada have lots of other people trying to get into them. So this isn't especially unique to data science. The OP is trying to determine what he can do to increase the probability that he can land a position outside academia.

I have already explained why wireless communication is (if not a dead end), very difficult to break into in Canada. So why not try to have him pursue where jobs are actually advertised (even if there is competition)?
My impression is that it's simply worse in Data Science than in most other STEM fields. Admittedly I don't have any actual numbers to back that up, it's just my impression from reading about the field. It's easy for companies to hype it up like "the future is here! Artificial Intelligence!" and it's vague enough that anyone with anyone with any sort of STEM degree is kinda-sorta- qualified. Basically I agree with what the OP said:

I feel that the Data Science field is very competitive, because it seems that all people try to get in because of the hype around it, and I have little to no chance there in this wave, although I have been developing some related skills in Python and did some personal projects. Also, in my experience people are not willing to connect with me, maybe because I don't have much to offer in that area. One senior data scientist was nice enough to meet with me to edit my resume to look appealing for data science positions, but that was about it.
For someone who already had a job and was thinking about trying to make a career switch, or a student thinking about a potential future career, I think DS could be fine. But it sounds like there's a lot of time pressure here- he wants to find a job ASAP. Trying to learn and break into a highly competitive field takes time.

To try and be constructive- he might have success getting a data *analyst* job. I think he would meet the requirements for a lot of those jobs. Kind of seems like a waste of a PhD though...

I have to ask- why is the Canadian government these highly specialized PhD programs in dead-end fields? Surely there could be a better way to use smart, dedicated students and 4+ years of funding.
 

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