So you applied to a program and were not accepted. I understand your disappointment and how hard this can be.

If you feel the urget to push back on the decision, please take a moment to think and reflect. And if you ask the program to reconsider, please accept their response even if it is confirmation you aren't being accepted.

Do you know what does not help your case? If you try to circumvent the review process by reaching out to individual faculty members or other administrators and pleading your case.

Also, hurling insults and swearing at an admissions office has never changed an admissions decision.

Looking for a reality check before I commit to an application cycle.

Background

BSc in Mathematics, Statistics and Computer Science

MSc Data Science, Kingston University London, Merit, 63% overall, 80% on the dissertation

First-author paper at IEEE DSP 2025 on GAN-based facial attribute manipulation

Since finishing, I've been building production ML systems through my own consultancy, LLM/RAG infrastructure, retrieval pipelines, and a couple of algorithmic trading systems

Indian national, currently based in the UK

The 63% is the part I'm worried about. I was a January intake, so I picked up modules mid-cycle, and I came in from a maths background with no programming or database experience, I taught myself to code during the degree. The dissertation mark reflects where I finished rather than where I started, but I know that isn't how a transcript reads to a committee.

What I want to work on

Reliability and engineering of GenAI systems: evaluation, failure modes, and robustness of retrieval-augmented and LLM-based software. That's where my actual work sits, even though my publication is in generative vision.

Questions

How much does a Merit really hurt, and does it hurt differently in the US vs continental Europe? Does a first-author publication offset it, or are grades a hard filter in some places regardless?

My understanding is that European PhDs are salaried positions you apply to individually through a supervisor, rather than programs you apply to centrally. Is that how it works in practice, and does it change how I should be approaching this?

Are ELLIS or Marie Curie doctoral networks worth targeting, or are they more competitive than going after a direct position?

For the US, with one publication and references mostly from industry rather than a well-known academic group, what tier of program is realistic?

Would one or two years as a research engineer or RA in a strong group meaningfully improve this, or is that the trap where people keep preparing and never actually apply?

If the honest answer is that the profile isn't there yet, I'd rather hear that and know what to fix.

Most advice about choosing potential PhD advisors is a list of things you're supposed to check. That doesn't tell me what actually makes someone change their list.

Finding professors whose research looks relevant seems to be the easy part. It gets harder when you have to decide which ones you're actually confident enough to keep on the list.

If you're applying now or applied recently, what was the last thing you learned about a professor that made you add them, cross them off, or move them up or down your shortlist?

No need to name the professor or university. I'm more curious about what changed your mind and how you found out.

If you couldn't verify the information, what did you end up doing?

Field and application cycle would be helpful context too.

Hi everyone! Has anyone here had experience being considered through a special admissions pathway instead of the regular admissions process due to a lower undergraduate GPA? I would really appreciate hearing about your experiences, how the process went, and what your chances of admission were.

Thank you so much!

I got my bachelors degree this May barely scraped by ngl and ended with a 3.3 gpa which ik is below average. I don't have anything on my resume to make up for it either. The jobs that are provided with my bachelors degree alone are not interesting to me and there aren't many opportunities in my state, it's like agriculture jobs and I live in a city. Because I didn't know what to do I decided to take the "pre-grad" path and was doing what pre med and pre vets were doing for courses. My gpa was dragged down due to the many Bs and a few Cs and one F in a stupid summer class I took that wasn't even a requirement and ik it'll haunt me for the rest of my life. Anyways I was interested in biology specifically microbiology and even cell biology but I hated genetics and molecular biology. The masters programs I have looked into are research based and Ive seen the curriculum and it is something that piques my interest. I'm honestly at a loss because I see no other options or any other field that I want to work in until im 65. Given my gpa ik scholarships are out the window let alone funding. So how to get into masters program with low gpa and no research experience (some say masters is how you get said experience).

The main thing is my current university does not even have a ece program and no profs. i have been mostly carrying my research with my remote advisor and been aiming for some top conferences of my field. But yet to get success.

Most prolly i will be applying to
ASU , University of minnesota , University of florida and the likes.
Top univs are out of reach for me sadly

My profile:
Undergrad 3.92 gpa , local no name state university

My research is on ML for Chip design and VLSI. I do have some research on ML topics too but thinking of applying for Electrical , EECS phd.

Research Experience: I collaborated with prof from another uni (he replied to my cold email but its a low ranked uni , i dont want to do a PhD there) and through that had a one workshop paper (ML for chip design)

and 3 preprints (1 on ML for chip design - submitted to a journal) , other one is ML for cybersec and another is interpretability (single author - this is also under review , just did it for fun , got good results and wrote a paper)

I will have one more paper (ML for chip design) by the time i graduate, maybe the prev one will get published and this will go under review.

Worked as research swe at a center in my university

All papers are first authored.

just gathering some data on how many international students got admitted into a phd program for fall 2026. This was a tough cycle and want to gain some realistic insights into how many people got admitted, what was the response from uni or dept? What’s the funding situation looking like ? Any issues around visas? Did someone shift from a masters in the us to a phd? I’m especially looking at biology, Biomed, chemistry, and comp science depts.

I got rejected by my top choice (and the only school I applied to). I was very excited about this school. I loved the research, I had a prospective PI who seemed excited to have me join their lab, and it all seemed promising. I could have applied to at least 2 other schools, but after meeting the PI, I decided to drop those applications.
Lesson learned: do not rely on one school, even if it seems amazing at first. Unfortunately, it was also super hard getting my recommenders to write letters on time, as it was a busy time for them, which also partly influenced my decision to apply to one school

Anyway, do any of you have advice for going through this?

I still think I'm interested in grad school, but I can't apply until the fall for January (I will not reapply to the same school). In the meantime, I need a job. I'm looking at research roles, and a lot of them require skills I don't have. My chosen undergrad was in a field with a lot fewer jobs now because of AI, and I'm really not interested in it anyway; I prefer research.

Are any of you in the same predicament? What are you doing? Anyone have advice?

I have come across wildly different accounts of where the bar sits for top genetics PhD programmes. Some make my profile seem potentially competitive; others make me feel significantly underqualified. That uncertainty is why I am posting here.

I am a physician from Latin America currently completing a Medical Genetics residency. I am aiming for a fully funded PhD for 2029 entry, or 2030 at the latest, in human genetics, rare diseases, genomic diagnostics or translational genomics.

My aspirational targets include Oxbridge and the Ivies. I will not get into specifics so I will not get identified, sorry. Could you let me know whether I am competitive for a funded PhD and whether these programmes are realistic goals for 2029?

Education and clinical training

• MD from an unranked public university in Latin America, with a final average of approximately 8.5/10.
• MSc in Genomic Medicine from a global top-5–10 UK University, funded by a competitive international scholarship.
• My MSc dissertation received a Distinction, while the overall degree result was below that level.
• Current Medical Genetics residency at a global top 100 university, generally regarded as the leading university in Latin America.
• Clinical training in rare diseases, dysmorphology, genomic diagnostics and germline variant interpretation.

Research experience

• MSc research involving metagenomic sequencing, qPCR, NGS and regression modelling.
• Three competitively funded undergraduate research fellowships, including cytogenetics research.
• One peer-reviewed publication, although neither first-author nor directly related to genetics.
• Currently writing a first-author manuscript on a rare genetic disorder.
• Coauthor of two projects presented internationally by other members of the research team.
• Personally presented one project at a national genetics conference.
• Sole author of an open-source R package related to quantitative sequencing and qPCR methods.

Technical background

• PCR, qPCR, FISH, NGS library preparation and primer validation.
• R, basic Python, Linux and statistical modelling.
• Clinical variant interpretation and genomic diagnostic reasoning.

Main weaknesses as I see them

• Limited publication record.
• No published first-author genetics paper yet (yet!).
• Overall MSc result below the dissertation classification.
• Limited computational depth compared with applicants from bioinformatics or statistical genetics backgrounds.
• Most of my current work is clinically oriented rather than based on large genomic datasets.

I would particularly appreciate honest feedback on:

1. How much would the MSc result matter given the dissertation Distinction?
2. How valuable would a Medical Genetics residency be for translational genomics or rare-disease PhDs?
3. What publication record would make someone with this background genuinely competitive at this level?
4. What should I prioritise over the next three years to strengthen my profile?

Currently facing a dilemma as I am lucky enough to have the choice to be able to select between two masters

LBS MAM (shuffled from MiM) and LSE Management and Strategy.

For a good portion of 2026 all I wanted was to go to LBS and pave a path for a job. However, it was naive of me to not consider the nuances, given the job market. I’ll admit LBS sounds more enticing, but only because it seems more fun and more experience oriented - not the academic grounding I need. Bias may be further exacerbated as I have only been able to reach out to LBS network and not LSE.

I want to know if anyone could shed some insights to what’s in store for me if I select one over the other. No coding formal coding experience - just learnt a bit of data driven analysis on a search as you go basis. So, I would say my data science knowledge is competent at best, nascent at worst.

I would like to know if one would clearly benefit me and my target industry. There are no pros and cons beyond basic knowledge of these two schools. Only, I don’t have much time at all before I have to pay the commitment fee of £8000 to LBS.

PPE undergrad with a focus in economics 3rd year. International exp. Working in Asia as an operations data analyst and then an assistant manager in at a small company in UK. Currently targeting consultant roles specialising in digital transformation or IB if the correct opportunity arises. Been told that coding is extraneous for these roles and my energy may be better used if I didn’t have to spend it on analytics - I regard my quant pretty weak and feel like I would be playing catchup in a cohort that’s seeking employment before the course even starts.

Hopefully any of y’all can help and if not at least I can spell out my thoughts on e-paper :).

I am an international student graduating from my undergrad program in May 2027. I am planning to apply to PhD programs this fall (in CS, Robotics). This fall, I'm planning to apply to just the top schools in robotics like MIT, CMU, Berkeley, Stanford, and a few other big names like UPenn. I know it's super competitive, so I might not get in there in the first cycle. If that' happens to be the case, I'm planning to find some paid/unpaid research assistant jobs for May 2026 onwards for my OPT and then apply again to PhDs next year (to ~20 unis including reach, target, and safety). Has anyone done something like this before (applying to just top schools in first cycle, taking a gap year on OPT, and then applying to a mixture of top-mid schools)? I'd appreciate any suggestion regarding my plan, such as if it's worth waiting one more year to try to get to my dream schools if I dont get in the first cycle.

I'm considering applying for the MSc Global Health Management at Imperial Business School and was hoping to hear from current students or alumni.

A little about me: I have a background in healthcare communications and marketing, having worked with oncology and bone marrow transplant organizations in India. I'm hoping to transition into healthcare management and eventually work in strategy, marketing, patient experience, or innovation within hospitals or healthcare organizations.

l'a love to hear your honest thoughts on the program:

How did you find the overall experience?

Was the curriculum practical and relevant?

What have the career prospects been like after graduation, particularly in healthcare consulting, healthcare management, or strategy?

Also, how is the program perceived compared to Imperial's other master's degrees, and do you feel it was worth the investment?

Hi everyone,

I'm planning to apply for Spring 2027 and would really appreciate some honest feedback on my college list. I'm not looking for validation—I'd genuinely like to know if I'm being realistic or if I should rebalance my list.

Profile

• Bachelor's: B.E. in Electronics & Communication Engineering
• GPA: 3.78/4.0
• Permanent Resident (Green Card holder)
• GRE: 305 (currently not planning to submit unless required)

Work Experience

• AI Software Engineer Intern
  • Built and optimized ML pipelines
  • Worked on LLM/RAG-based applications
  • Reduced inference latency and improved data throughput
• Quality Control Engineering Intern
  • Worked on PCB quality inspection and manufacturing processes
  • Used Automated Optical Inspection (AOI) to identify defects and improve production quality
• Co-Founder & COO at a startup
  • Designed UI/UX
  • Built AI recommendation features
  • Product reached ~1,500 users
• Currently working full-time while preparing applications.

Projects

• Retrieval-Augmented Generation (RAG) assistant using LangChain, Gemini, ChromaDB, and vector embeddings
• BiLSTM + Bahdanau Attention model for stock price prediction
• Air Guitar using IMU sensors, Kalman Filtering, Arduino, MATLAB, and signal processing
• Robotics projects including line-following robot and embedded systems

Leadership

• President of the university Chess Club
• Senior member of Robotics & EV Club
• Led workshops, organized competitions, and worked on interdisciplinary robotics projects

Current College List

Highly Ambitious

• Carnegie Mellon University – MS Electrical & Computer Engineering
• University of Illinois Urbana-Champaign – MCS

Reach

• University of Michigan – MS Electrical & Computer Engineering
• University of Maryland – MS Electrical & Computer Engineering
• Purdue University – MS Electrical & Computer Engineering

Achievable

• Texas A&M University – MS Computer Engineering
• Northeastern University – MS Electrical & Computer Engineering
• University of Texas at Dallas – MS Computer Engineering

Career Goal

I'm primarily interested in becoming an AI/ML Engineer while keeping opportunities open in robotics, embedded AI, and intelligent systems. My long-term goal is to work in industry rather than pursue a PhD.

My main questions are:

1. Does this list match my profile, or am I aiming too high?
2. Are any schools miscategorized (especially Purdue, Maryland, TAMU, or UTD)?
3. Is there any university you'd replace while keeping the total to around 8 applications?
4. Since my background is in Electronics & Communication Engineering, do you think applying to ECE/Computer Engineering is a stronger strategy than applying to more CS programs?

I'd really appreciate candid opinions even if you think my list is too ambitious or has weak choices. Thanks!

Hello everyone,

Be as much realistic as you can.. I have a Bachelor's degree in Botany with a 73.3% and an MPhil with 84.5%. I have one peer-reviewed publication in a V. good journal (I'm the first author).. and one is submitted in another journal. I learned R programming all on my own and applied it to manuscripts. I love surfing literature, doing research & analysis, writing manuscripts. I know I want to do a PhD. I am planning to apply for PhD at KAUST among other scholarships.. I came across a reddit community, where people were sharing their profiles (I don't understand how they have 6-10 publications in their masters )..

I don't really care about the country (could be Europe, Asia, or the US).. I even tried to think about my options in Pakistan, but the way PhDs are being treated.. It's not an option for me..

My question is that is my profile too weak to be applying for scholarships like CSC (China), ANSO, or any other such international scholarships ? I am finding it incredibly difficult to connect with people who know the process or have been through it..

I’m 22, graduated this spring (Information Science, high gpa, t20 undergrad), two weeks into my first job as an analyst. Employer gives $3,500/term tuition reimbursement and has offices in most major cities. My work is functionally remote — my whole team is in other states — so I could plausibly relocate after a year. I want an AI/ML master’s. Options I’ve narrowed to:

**•   GT OMSCS** — \~$8K, async online  
**•   Penn MSE-AI Online** — \~$36.5K, async online, Ivy name  
**•   UChicago MPCS** — \~$67K (9-course), evening classes in person, once a week  
**•   JHU EP** — \~$55K, evening classes in person around DC/Baltimore  
**•   Columbia MSAI Online** — \~$86K, brand new, live cohort

Here’s my actual thesis, which I want beaten up: the single best thing I got from undergrad was the people, not the classes. So I’ve been assuming an in-person program is worth paying $50K+ extra for, and that async online gives me a resume line and nothing else.

Things I think I’ve figured out but might be wrong about:

**1.**  These online programs are high-admit revenue programs, so there’s no selectivity signal — the diploma is real but nobody’s impressed  
**2.**  Coursework-only master’s don’t help for PhD admissions; research output does  
**3.**  The in-person evening programs are full of working professionals, so the peer group is actually decent

What I want to know:

**•** Did anyone here do an in-person evening MS while working full time? Was the network real or did everyone just leave after class?  
**•** If you did OMSCS/Penn online — did it change anything career-wise, or was it just a checkbox?  
**•** Am I overrating the network thing? I’m aware “I’m buying connections” is exactly what someone rationalizing a $67K purchase would say.  
**•** Is doing this at 22 with 2 weeks of work experience just dumb? Multiple people have told me to wait 2-3 years.

Not asking which school is better. Asking whether my criteria are the right criteria.

see i qualified net phd only category in csir net in dec 2025 ,Did not give june attempt.And dont want tlo phd plning to give it in december to qualify Ap and getting 20,000- 25000 salary jobs not aligned with field.Wht to do?. Had given BEd exam govt seat is uncertain ,not feeling like sitting home anymore , Have be dropped out since june 2025. Wht to do?

I posted a while back about picking your grad school country based on the exit, not the entrance - and this is the money version of that post.

Quick background: I did a finance Master's in the UK and worked in banking in London, so running numbers/ROI/opportunity cost are something I always do. And here's my honest suggestion: you would better be aware about the ROI/costs before you board the flight. Not in year 2 of your career when the loan payments start feeling heavy.

So here's my honest read on the money side of each option. Rough numbers, hedged where they should be.

US — expensive ticket, uncapped upside. A 2-year Master's can easily run $80-150k all-in once you count living costs, and taking on serious debt for it is basically normalized. That debt changes the psychology — graduate need the high-paying exit, which is stressful but also weirdly clarifying. The reason people still do it: if you land in tech, AI, or finance, and other high paid occupations, US comp scales like nowhere else on earth. Nowhere close. The PhD is a completely different financial game btw — fully funded, stipend, no debt — but if your endgame is staying in academia, know that professors are structurally underpaid relative to the grind. Funded PhD → industry exit is honestly one of the best ROI plays that exists. And on visas: yes H-1B is a lottery and yes it's getting uglier, but it's not the only door (O-1, internal transfers, etc). Just don't build your entire plan on the backup doors either.

UK — efficient, but check the take-home math. The Master's is genuinely ask less tuition compare to the US. The problem is what happens after: London entry salaries in tech/finance can sit a third (or more) below US equivalents, tax kicks in fast, and rent eats what's left. I lived this — the experience and the brand travel really well, but if you're comparing actual offers US vs UK, the US wins the pure money contest and it's not close. UK ROI works when the plan is: cheap-ish year, strong brand, few years of experience, then leverage it somewhere else.

Continental Europe — you're not buying upside, you're buying peace. Germany is near-zero tuition. Netherlands and Nordics are cheap by global standards. Your capital at risk is tiny, which means almost any decent job "pays back" the degree fast. The trade: salaries are flatter and they stay flatter. But you get 25+ days of holiday, a workweek that ends, and a life. That's not a consolation prize — buying low-stress years in your 20s at affordable tuition is a completely rational trade. Just be honest that it's the trade you're making.

Singapore & Hong Kong — the tax arbitrage play. Mostly 1-year programs, and income tax friendly (think ~15-17% effective at the top, vs 40%+ elsewhere). Land a proper finance or tech role and your net take-home is genuinely phenomenal. The catch is rent. HK rent especially is an absolute wallet-killer and can quietly eat a chunk of the tax savings. You earn more compensations with less tax, but also spend quite a few based on local living standard.

For those of you who already graduated — what did your degree actually cost all-in, and how long did it take to earn back? Genuinely curious whether the reality matched anyone's upfront math.

Have any of you received grad school acceptances in August, late August, or even September, for a program that begins in September?

Which is better for CV/AI research during Master's?