Hi—

As I learn more about competitive the enrollment process for PhD is, I am widening the range of schools I apply to for Biostats PhD. I am too broke to go for a masters so going straight into PhD after undergrad is the only viable option. I was wondering what people thought about the program at SUNY Buffalo? I am meeting somebody at UPenn that did their PhD there and it made me curious as to how the program up there is.

Would appreciate thoughts.

Thanks

even if i'm finishing grad soon, i still have no idea how to get to employment at all.

How do you all do that?

i'm mostly seeking hospitals, or any research organization.

(ps.

current state: i've been only working on publishing papers that are not really sophisticated but showcase some workflows used in hospitals.

my

Now i'm getting worried if this is right thing to do at this time.)

Hi everyone, I'm trying to break into the field of Biostatistics coming from a Data Analyst background (with an MS in Mathematics). To help improve my marketability as a candidate, I'm interested in volunteering somewhere. Any advice on where to look for these opportunities and how I can find something that will increase my marketability for future Biostatistics jobs?

I currently am getting a masters in exercise science and have been very research heavy since my undergrad. I originally wanted a PhD in exercise science and still may get that but I saw that I could get another masters in biostats and potentially make more money/get hired easier. What is your guys’ experience and does it seem worth it?

Hello. I am an honours graduate in Psychology in Australia. I am considering applying for the master of biostats in Sydney/melbourne, however I wanted to ask earnestly about the mathematics. I have never been notably talented at maths (I’d say just above average, 6/10). Although, I do excel in statistics. I have only completed undergrad + Hons level psych statistics though and come first in my class for each statistics unit. I have not done any pure maths since highschool many years ago, and I would be a bit nervous to begin as I always leaned more towards English.

My two questions are, if I put in the extra work, do you think I will be able to keep up? Do I need a natural affinity for maths to land a job and complete this course?
Also, are there available jobs (happy to work in any biostatistical field) in Sydney? Or is it extremely competitive?

Thank you.

Is bs stat still worth it to pursue now that AI is widely used??

Hi, so I'm [21M] a CS graduate with a minor in Bioinformatics. I'm currently working at my internship at a startup in a ML Research/Engineering role (it's a bit of both, & SDE too).

I wish to get into Biostatistics and Bioinformatics, to help expand my overall understanding of ML from a research focused perspective, I don't want to pursue a career in it, I am just interested in the field. I am willing to put in the hours, but I'm not sure what would be a good entry point.

I have studied Biological Databases, and simple Bioinformatics Pipelines (scRNA, BulkRNA, Pseudo-Bulk, MicroArray etc), in my courses.

About Me: I am graduating this year, I have one journal publication in a journal by IoP (Mechanical Engg + ML), I am familiar with writing CLIs, ML frameworks, and have worked with real world data for Voice, Vision, Text, Multimodal and Time Series.

PS: I apologize for my terrible English, It's not my first language.

I’m looking for some career advice from biostatisticians or people working in academic research.

I recently finished my M.S. in Biostatistics and have a series of interviews for a biostatistician position at a university. The role would be embedded within a cardiovascular research lab working with genomic data related to heart disease, rather than in the university’s central biostatistics department.
My background is a little unconventional. I have a B.S. in Microbiology and nearly a decade of experience as a medical laboratory scientist, so I’m very comfortable with the biological and clinical side of research. During my master’s program I worked with mostly with R and a little bit of python and SAS, my thesis involved analyzing the MIMIC-IV database.

Where I’m feeling intimidated is my programming and statistical depth. I don’t consider myself a strong programmer (especially compared to people coming from statistics or computer science backgrounds), and while I understand the statistical methods I learned in graduate school, I still feel like there’s a huge amount I don’t know.

I had originally hoped my first job would be in a biostatistics department where I’d be surrounded by experienced biostatisticians and have more mentorship. Instead, this position would have me working directly with a research lab as the biostatistician for that particular lab. I’m worried I’ll be expected to be “the statistics expert” from day one, even though I still feel like a beginner. Also, they want most work to be done in python, which I feel not as confident working with relative to either R or SAS.

For those of you who work in academic research labs:
Is this a common feeling for new biostatisticians?
How much mentoring do embedded biostatisticians typically receive?
Were you expected to already know everything, or did you learn a lot on the job?
Is working directly in a research lab as a first job a good career move, or would it be better to hold out for a position within a biostatistics department?

I’d appreciate any honest advice or experiences. I’m excited about the opportunity, but I also don’t want to get in over my head.

Hi, everyone. I am a first-year PhD student in biostatistics. Previously, I got my bachelor's degree in Math and Stat. It is my first time getting into this field. After talking with some senior PhD students, I found that maybe clinical trial design and causal inference could spark my curiosity. And I hope to get into industry after graduation. Do you have any advice for me? Thanks a lot in advance.🥹

I have an M.S. in Statistics and 28 years of experience working as a statistician in the federal government. During my career, I have worked for several government agencies, applying statistical methods to a wide range of projects.

I would like to transition into the field of biostatistics, but I'm not sure where to begin. What are the least time-consuming and most cost-effective pathways to make this career change? Which biostatistics certificate programs are currently the most respected and valuable in the field?

What steps would you recommend I take to successfully transition into biostatistics? What Certs are recognise in the feild.

Hello! I'm not sure if this is the correct place to ask this question (I am a lowly field ecologist who has been forced to open R, my apologies).

I have a large dataset where I need to compare the number of bird calls detected against a bunch of different factors (wind speed, precipitation, temperature, moon phase, etc.) and I plan to run a glmer model to do so. I'm having trouble with determining which "family" I should use.

The data was recorded nightly, and I have 30 nights for the first set and 26 for the second. The bird calls are whole numbers, but many of the environmental factors are decimals. I do have values of 0 (such as 0 mm of precipitation), and I have negative numbers but that's only for the moon data (numbers in reference to the horizon, which is 0).

My professor in passing told me to use poisson, but after being confused looking at the differences in the families I'm not sure if this is correct. I don't think the data is on a normal bell curve, and the sample sizes are pretty small. I'm really just struggling to understand the differences between the families so even if someone could semi-simply explain them I can probably figure out which one works best.

I can answer any questions, and if this is the wrong place to ask this I apologize, please point me in the right direction. The sub rules say no homework help, I promise this is for my research and not homework.

Thank you!

I'm starting my Master’s in Bioinformatics at GSU this fall! As an international student, I’m planning ahead and looking to secure an internship for Summer 2027.
I have a strong background in mathematics and statistics, and I’m focusing on computational biology and data analysis.
Are there any local Atlanta biotech companies, research labs, or remote-friendly organizations that regularly hire bioinformatics interns? I’d love to hear about any leads, networking events, or general advice on when and where to start applying.
Thanks!

Hello everyone, I am 22 M bsc statistics graduate thinking to pursue msc biostatistics in India, i am really unsure about job market in biostatistics, is it a good career choice and plus can you rank good colleges for biostatistics in placement wise and give clear picture

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Hello everyone, I have some questions about pursuing a PhD in Biostatistics and am trying to get a better idea of the landscape. I'm trying to transition into public health and am thinking about trying for a PhD in Biostatistics. I have a Masters in Mathematics with a relatively competitive GPA (3.73 GPA during MS and 3.94 during BS in Mathematics). I've been working as a data analyst outside of public health for the past three years. I'm looking into potential PhD programs now and wondering if I'll be a competitive candidate with no research background.
Follow up question, is the GRE worth taking in my case? Time is at a premium for me right now.

Please suggest me college

I was watching YouTube videos on how to get research experience for post-grad applications, and they said you can get research experience remotely by cold emailing professors in engineering and computer science. So it didn't feel like a giant leap to assume the same for biostat.

Is this a viable option??? Had anyone else here gotten research experience remotely?

Not sure if this is appropriate for the sub so apologies in advance! I would really like to hear the opinions of other postdocs in genomics/bioinformatics/statistical genetics. I'm at a point where I'm thinking of applying for independent fellowships and funding, and it feels like success in this field basically hinges on having better cohorts with more individuals and more data layers measured than other people. And the output is always just a better list of genes/proteins with more accurate p-values that can help us get to new drugs, but actually developing these drugs is never really part of the job and everything feels so clinically removed? Is my research field kind of boring or is the grass always greener 😭😭 I'm always looking to the people doing generative genomics or somatic genomics and it seems a lot cooler.