u/Mindless_Farm3706

I'm looking specifically for PhD positions in Europe focused on spatial multi-omics (spatial transcriptomics/proteomics/epigenomics, e.g. Visium, Xenium, CosMx, DBiT-seq, COMET, MERFISH etc.), ideally applied to cancer/precision medicine.

Background: MD Pathology + MBBS, currently doing a self-directed computational biology sabbatical (bulk RNA-seq in R using TCGA data I ve been learnign for past 8 months and feeling confident in this now). Looking to combine the histopathology/slide-reading side with spatial computational work for a PhD.

I've found a few solid leads (KU Leuven's SPACE-MEL MSCA Doctoral Network) but honestly the pickings feel really thin when searching directly for "spatial" on portals like EURAXESS and CORDIS. My hunch is that most spatial-omics PhD work is buried inside broader listings (computational cancer biology, precision oncology, systems biology) rather than branded explicitly as "spatial."

A few questions for anyone who's been through this or is in the field:

• Are there labs/institutes you'd flag as strong for spatial multi-omics that I might be missing (Human Technopole, Sanger, EMBL, individual PI labs, etc.)?
• Any go-to search strategies beyond EURAXESS/FindAPhD/CORDIS?
• Is spatial multi-omics still too young a subfield for dedicated PhD tracks to be common yet, or am I just searching wrong?

Any pointers — labs, PIs, programs, or even just "you're overthinking this, here's how people actually find these" — genuinely appreciated.

Should I cold email every PI who has worked with spatial data or how to make this work ?

Hey everyone,

Quick background: I started learning R from scratch earlier this year — literally couldn't write a single line before. Worked through it steadily and I'm now comfortable doing bulk RNA-seq analysis (DE analysis, normalization, batch correction, that whole workflow).

Now I want to branch into single-cell RNA-seq analysis, and it looks like most of the ecosystem (Scanpy, AnnData, etc.) lives in Python rather than R. Problem is, I don't know Python at all yet.

For those who've made a similar jump — is there a sensible path to go from "no Python" to "comfortable doing single-cell analysis"? Specifically:

Do I need to learn general Python properly first (like I did with base R), or can I learn it "on the job" through a scRNA-seq-focused course/tutorial?

Any go-to resources — courses, books, GitHub tutorials — that take you from Python basics through to Scanpy/single-cell workflows specifically?

Is prior R/bulk RNA-seq experience actually transferable conceptually (QC, normalization, clustering, etc.), or is single-cell different enough that I should treat it as starting fresh?

Roughly how long did it take you to get functional?

Appreciate any pointers — happy to share my bulk RNA-seq learning path too if it's useful to anyone in a similar spot.