$211,910top of the range in District of Columbia · middle $98,920 / yr
AI augments this role
Mycologists in the United States earn a median of $98,920 a year. Pay starts near $60,430. Pay reaches $211,910 at the top of the range in Washington D.C., the best-paying location for this work among those with at least 500 people in the job.
Source: U.S. Bureau of Labor Statistics, Occupational Employment and Wage Statistics, May 2025 (Biological Scientists, All Other, SOC 19-1029). Last checked 9 September 2026.
Entry level
$60,430
Top of the range · District of Columbia
$211,910
Education
Master's or Doctoral degree in Mycology
Wages — U.S. Bureau of Labor Statistics, Occupational Employment and Wage Statistics, May 2025 (Biological Scientists, All Other). Top of the range is the highest state-level figure among states with at least 500 people in the job. AI-impact rating is PayCrunch's editorial assessment. Updated September 2026.
🆕 New & Trending AI Tools for MycologistReviewed September 2026
We track new AI-tool launches every week and refresh this list — here’s what’s gaining traction for Mycologist work right now.
Julius AINEWFree / $20 mo
AI data analyst that runs statistics and charts from plain-language prompts.
How a Mycologist uses it: analyze datasets and generate figures without writing code
NotebookLMNEWFree / $7.99 mo
Google tool that answers questions grounded only in the documents you give it — with citations.
How a Mycologist uses it: load your own manuals, policies, or PDFs and ask questions that stay accurate to the source
ElicitFree / $12 mo
AI research assistant that finds and summarizes papers.
How a Mycologist uses it: run a literature review and extract findings across dozens of papers fast
ConsensusFree / $9 mo
AI search that answers questions from peer-reviewed research.
How a Mycologist uses it: get evidence-backed answers with the studies behind them
SciSpaceFree / paid
AI that explains papers and helps with literature review.
How a Mycologist uses it: decode dense papers and trace citations quickly
SciteFree / $20 mo
Shows whether other studies support or contradict a paper's claims (Smart Citations).
How a Mycologist uses it: check if a finding is actually backed by the wider literature before you cite it
ChatGPTFree / $20 mo
The most-used AI assistant — writing, analysis, research, and images from a plain-language chat.
How a Mycologist uses it: draft emails and documents, summarize long files, and get instant answers to on-the-job questions
ClaudeFree / $20 mo
AI assistant known for careful writing, long-document analysis, and coding.
How a Mycologist uses it: analyze big reports or spreadsheets and turn messy notes into clean, finished writing
Google GeminiFree / $20 mo
Google's AI assistant, built into Gmail, Docs, and Search.
How a Mycologist uses it: draft and reply inside Google Workspace and research without leaving the page
A mycologist is a fungus scientist. The subject is the kingdom of fungi: what lives in a forest, what shows up in a food plant, what a campus lab is funded to study, and how that knowledge gets written so a manager or a student can use it. The hire is usually a degree plus a record of careful work. The employer is often a forest service or another land agency, a food company, or a university. The day is reports, collections, classes, and meetings with people who are not specialists. It is a scientific career, not a weekend hobby with a basket.
Fungi, as a job rather than a hobby
Hobby knowledge and a job diverge at the point of accountability. A club walk can celebrate a find. A mycologist on a payroll has to say what was observed, where, under what limits, and what a land manager or a product team should do with the statement. The work product is a survey note, a species account, a teaching lecture, a dataset, or a memo that a non-specialist can act on. Curiosity is the start. The career is the discipline of making the curiosity checkable.
Field days and desk days alternate. On a field day you travel to a site a project already defined, record what you see, label specimens for a collection, and note the habitat in language another scientist can follow. On a desk day you identify material against references, enter records, write, and answer the collaborator who needs a plain-language version. University weeks add office hours and seminars. Food-company weeks add meetings with quality and product staff who want a scientist's judgment, not a lecture. The through-line is fungi as the subject and writing as the proof.
Collaboration is constant because fungi sit next to plants, insects, soils, and human food systems. A forest project may pair you with a botanist or a wildlife biologist. A campus project may pair you with a chemist or an ecologist. A food company may pair you with engineers who run a plant. Your value is knowing the fungal side well enough to tell those partners what is known, what is uncertain, and what would be a reckless claim. Overclaiming is how specialists lose trust. A short, accurate memo beats a dramatic one.
Neighbors, reporters, and park visitors ask what they found, whether you invited the conversation or not. Part of the professional stance is knowing which answers belong in a casual conversation and which belong in a formal identification with a specimen and a record. You also learn to send people to physicians or to poison-control resources when the issue is a human health emergency. That boundary is part of being a scientist in public, and it keeps your job from pretending to be a clinic.
The degree employers actually read
What stands in for a licence
There is no single national licence that makes someone a mycologist. Employers hire on a biology degree, graduate training when the role is research or teaching, and a record of supervised scientific work. The degree proves you can handle the science. The record proves you have already done a version of the job.
A bachelor's degree in biology, mycology, botany, plant pathology, or a close field is the usual door for junior scientific roles, survey crews, and some industry posts. A master's degree deepens a specialty and is often what a food company or an agency wants when the seat includes independent writing. A doctorate is the common path into a university faculty job or a research lead who designs studies and mentors others. The title on the diploma matters less than whether the training was actually about fungi and whether a supervisor will say so in a letter.
Preparation looks like coursework in biology, ecology, and the organismal science your program requires, plus time in a lab or a field crew where you learn how that group keeps records. A thesis, a senior project, or a stretch of paid technician work gives you something to describe in an interview without handing over your employer's confidential files. Publications help for academic jobs. For an agency or a company, a clear report you are allowed to share, or a precise description of your role in a larger study, often matters as much as a journal name. Keep specimen logs, course lists, and supervisor names in one folder. Hiring moves slowly, and memory is a bad archive.
People sometimes try to skip the degree because they know a lot of species from personal study. That knowledge can be real and still fail a posting that requires a degree for legal, grant, or credentialing reasons inside the institution. If you are coming from a different science, the bridge is formal coursework plus a supervisor in mycology who will put your name on legitimate work. Short workshops can add a skill. They do not replace the degree a forest service, a food company, or a university listed in the advertisement.
A forest, a food company, or a campus
A forest service or land-agency hire puts you on landscapes the public already owns. The job may be a survey of fungi in a habitat the agency manages, a contribution to a management plan, or identification support for staff who found something they cannot name. You work under the agency's chain of command, you file reports in their format, and you may spend part of the year in the field and part at a desk. Seasonal appointments are common early on. A permanent seat comes when you have shown you can finish a project and explain it to a ranger or a planner who will never become a mycologist.
A food-company hire puts a fungus scientist next to quality, product, and plant staff. Your role is to interpret fungal problems the business already has: spoilage that keeps returning, a process that depends on a fungus, a supplier issue that needs a scientific opinion. You write, you sit in meetings, and you say when the evidence is too thin for a confident claim. You are not the person who runs the factory floor. You are the specialist the floor calls. Confidentiality is part of the employment deal. A story that would impress a conference may be a trade secret, and you learn the difference before you update a public profile.
A university hire splits among research, teaching, and service. Early on you may be a technician, a graduate student, or a postdoctoral researcher inside someone else's program. Later you may lead a program, advise students, teach a course, and chase the funding that keeps the work alive. The public face is a lecture or a field course. The private face is data, manuscripts, and the unglamorous care of a collection. Academic jobs are fewer than the number of people who want them. Agency and industry paths are legitimate careers, not consolation prizes, and many strong mycologists spend their whole working life off campus.
Collections, herbaria, natural-history museums, and cooperative extension offices are neighboring employers. They need people who can name fungi, keep records straight, and talk to the public or to growers without drifting into medical advice. When you apply, name the setting you actually want. A letter that says you would be happy in any job that mentions fungi reads as unfocused. A letter that says you want survey work for a land agency, or fungal expertise inside a food company, or a teaching-and-research post, gives a hiring manager a reason to keep reading.
From a first study to a lead role
The first paid role is often support: a field technician, a junior scientist, a research assistant. You execute a plan someone else designed, you keep the notes clean, and you learn how that organization decides what is finished. Do that well and people invite you onto the next project. Do it carelessly and the degree will not save the reputation. Ask to own a small piece you can describe later: a site, a dataset, a section of a report. Ownership, even of a narrow slice, is what turns a helper into a candidate for a lead.
Mid-career work is designing the study or the survey, supervising newer people, and representing the fungal expertise in rooms full of other disciplines. In an agency that may mean a specialist title and a region. In a company it may mean the person quality leadership calls first. On a campus it may mean principal investigator, with students and a budget. The skills that travel are writing, supervision, and the habit of separating what you observed from what you hope is true. Those skills are also what you talk about when you change employers. The organisms change less than the audience.
Getting hired is a paper trail plus a conversation. Watch agency announcements, university job boards, and food and agriculture employers that list microbiology, plant pathology, or mycology. Tailor each letter. Bring a short account of one project: the question, your role, the limit of the conclusion, and what you would do differently. Be ready to explain your science to a non-specialist, because the person screening resumes may be a human-resources partner. If a posting requires a doctorate, do not apply with a bachelor's and a promise to learn. If it requires field experience, do not answer with only coursework. Match the advertisement, then let the interview go deep on the work you have actually done.
The high end in the District of Columbia, the median in Maryland
These wages are Occupational Employment and Wage Statistics for May 2025. The broader title, used once here because a mycologist often sits inside it, is Biological Scientists, All Other. Entry is $60,430. The national median is $98,920. The high end of the published range is $211,910 in the District of Columbia. That high end is not a state median. The highest median is in Maryland, at $121,680, a different statistic in a different place.
Further medians include California at $113,530, Washington at $108,110, and New Jersey at $104,750. The lowest median in this set is Missouri at $63,290. The gap between the highest and lowest of those state medians is $58,390. Entry to the national median covers $38,490. The national median to the District of Columbia high end covers $112,990. Maryland's median sits $22,760 above the national median. Read the high end as the top of a published range in the District of Columbia. Read each state figure as a median, the middle of the occupation there.
A new graduate comparing offers can set $60,430 beside $98,920 and ask which duties match which side of that $38,490 step. A technician role with close supervision belongs nearer the entry figure. Independent writing, a scarce specialty, or supervision of others is how people argue toward and past the national median. Someone recruiting you with the District of Columbia figure of $211,910 needs to show a role at the high end of the range, not a junior survey seat with a glamorous city attached. Maryland's median of $121,680 is the better local benchmark when the job is a typical one in that state and your record is solid.
Place still matters when the credential, meaning the degree, is the same. California's median of $113,530 and Washington's $108,110 both sit above the national median of $98,920. New Jersey's $104,750 does too. Missouri's $63,290 does not, and pretending a national median is a local promise will sour an offer conversation in a lower-paying market. Name the state you will actually work in. If you are choosing between an agency post and a company post, compare the duties first and the median second. A title bump with no change in responsibility is a weak reason to chase the larger number.
Naming a figure when the offer is real
Bring three numbers and one story. The numbers are the entry of $60,430 if you are new, the national median of $98,920 if you already work independently, and either Maryland's median of $121,680 or the District of Columbia high end of $211,910 only when the place and the seniority match. The story is a project you finished: what the fungal question was, what you personally did, and how the user of the report relied on it. Hiring managers pay for that reliability more than for a list of organisms you admire.
If an academic offer quotes a nine-month figure, ask what summer support looks like before you compare it with these annual amounts. If a company offer includes a bonus, ask whether the bonus is typical or exceptional, and still anchor the base to the series. Benefits, field travel, and whether the employer pays for conferences can change the value of a package. Compare them without inventing dollar amounts the series does not contain. Then return to the wage: $60,430, $98,920, or the state median that fits the job's location.
Keep the two headline places straight in your own mouth. The District of Columbia is where the high end of $211,910 was published. Maryland is where the highest median, $121,680, sits. Using one as if it were the other makes you sound careless with the only public figures you have. A fungus scientist who is careful with a wage table is easier to trust with a specimen record. That is the tone to take into the conversation, and it is the tone the work itself rewards.
The top of Mycologist pay — and how to get there with AI
$211,910what Mycologist pay reaches in District of Columbia
Highest state-level top-of-range annual wage for Biological Scientists, All Other, among states with at least 500 people in the job. U.S. Bureau of Labor Statistics, Occupational Employment and Wage Statistics, May 2025.
And the role it leads to — Data Scientists — reaches $224,920 in California.
$60,430entry$98,920middle$211,910top end
A mycologist who identifies and describes fungi by hand stays mid-range; the ones at the top built the sequence pipeline, the strain database or the analysis tool that the rest of the group now runs every week.
The paid version of this occupation is largely computational. Manipulating genomic and proteomic databases, developing data models, creating analytical approaches where none exist, and consulting with researchers on computational strategy are the duties that carry the salary. Fungal work makes this sharper than most, because identification, contamination screening and strain tracking all produce sequence data faster than anyone can curate it by hand. Whoever writes the tool that turns that flood into an answer becomes the person consulted at the design stage, which is where the pay actually sits.
Your playbook, by where you are now
Just startingGet your own analyses into code
Move every repeated identification step out of a spreadsheet and into a Bash script you can rerun without thinking.
Learn enough Bioconductor to run your own expression and community analyses rather than joining a queue for them.
Wrap each project in Docker so a result from two seasons ago still reproduces when a reviewer asks.
Keep isolate and strain records in Microsoft SQL Server with defined fields, not in a folder of workbooks named after people.
Ask Claude to explain an unfamiliar package's error before you interrupt a colleague, then read the source to confirm the explanation was right.
What proves it: A scripted, containerised analysis someone else in the group can run unchanged.
Realistic span: your first years after the degree
A few years inWrite the tool the group needs
Build the pipeline your group runs most often, sequence in and identification with quality flags out, and give it a version number.
Design the database behind it so isolate, substrate, collection site and sequence stay linked instead of drifting apart.
Run it on the Linux compute the group already pays for, and move to Amazon Web Services AWS software only when a run genuinely outgrows the bench.
Document what the pipeline assumes and when its output should not be trusted, in the repository beside the code.
Join experimental design conversations early enough to say what the resulting data will and will not be able to answer.
What proves it: A versioned pipeline cited in the group's methods sections.
Realistic span: years three through seven
ExperiencedSet the computational strategy
Direct the technicians and information technology staff running these tools, and review their output against a written standard.
Put a small Django front end on the pipeline so people who will never open a terminal can still submit a run.
Publish the method rather than only the findings, so the approach carries into other laboratories with your name on it.
Move the largest analyses onto Apache Hadoop where the data justifies it, and record the cost of a run beside its result.
Data science roles pay above this occupation and recruit directly from it; the District of Columbia pays this work best.
What proves it: A published method and a group whose computational standards you set.
Realistic span: year eight onward
The next 90 days
Find the analysis your group repeats most and time yourself doing it by hand once, honestly, including the fiddling. Then spend ninety days turning it into something anyone can run: a script, a container, a defined input format, and a short document saying what it assumes. Sequence identification against a reference set is usually the right candidate, because everyone needs it and everyone does it slightly differently. Release it internally and collect complaints. The complaints are the specification for version two, and by version three you will be the person consulted before an experiment is designed rather than after the data has arrived.
Wage figures: BLS OEWS, May 2025. The playbook is PayCrunch editorial guidance, not a guarantee of pay or placement.
Every figure is the national median from the U.S. Bureau of Labor Statistics (OEWS) shown on that role’s own page.
Never used AI before? Start here (2 minutes).
Start with the bioinformatics that turn sequences into species and genomes into leads. If you barcode fungi, learn to run an ITS metabarcoding pipeline — QIIME 2 or DADA2 against the UNITE reference database — with an AI coding assistant (ChatGPT or Claude) writing and explaining the commands. This is the single skill that scales a mycologist from identifying one specimen at a time to characterizing whole communities.
For the industry-facing side, open antiSMASH to scan fungal genomes for the biosynthetic gene clusters behind antibiotics, antifungals, and other metabolites — the discovery engine behind well-paid biotech work. Pair it with Elicit or Consensus (free/low-cost) for literature and you have the toolkit that separates a taxonomist's salary from an industry scientist's.
The one rule, forever: Fungi include human, animal, and plant pathogens and potent toxin producers, so treat biosafety and biosecurity as non-negotiable — an AI protocol is a draft, and containment level (BSL), permits, and select-agent rules are set by your biosafety officer, not a chatbot. Never let a model's species or toxin call stand unconfirmed: misidentifying an edible versus a deadly Amanita, or a benign versus toxigenic Aspergillus, has real consequences, so verify every AI identification with sequence data, culture, and expert review.
The plays — exact steps, exact prompts
Do these in order. Each one is copy-paste ready. You do not need to know anything about AI going in.
1
Run fungal metabarcoding pipelines with an AI coding partner
Why this pays: Characterizing whole fungal communities from environmental DNA is what agricultural, soil-health, and microbiome companies pay for. An AI coding assistant lets a mycologist who isn't a career bioinformatician run these pipelines properly — a skill that commands industry pay.
QIIME 2DADA2UNITE database
1
Set up an ITS amplicon workflow in QIIME 2 or DADA2, classifying sequences against the UNITE fungal reference database, with Claude or ChatGPT writing and explaining each command.
2
Get the pipeline logic right for fungi specifically, where ITS length variation breaks naive settings.
Copy-paste this prompt
I'm building a fungal ITS metabarcoding pipeline in DADA2 for [soil samples]. Fungal ITS varies a lot in length, so standard truncation settings can destroy real data. Walk me through the correct approach: primer removal (ITS region), why fixed-length truncation is dangerous for ITS, appropriate quality filtering, and taxonomy assignment against UNITE. Explain each parameter so I can defend it, and flag the mistakes that inflate or lose diversity.
AI writes code that runs even when the biology is wrong. Confirm parameters against current ITS best practice and sanity-check diversity numbers against known controls.
3
Include mock-community or positive controls and report them, so your diversity estimates are defensible to reviewers or clients.
What you'll haveCommunity-scale fungal characterization done rigorously by one scientist — the applied skill industry hires for.
2
Mine fungal genomes for drug and enzyme leads
Why this pays: Fungal secondary metabolites are a proven source of antibiotics, antifungals, and industrial enzymes. Using genome-mining AI to surface promising biosynthetic gene clusters is the discovery work that drug-discovery and biotech firms fund at the top of the pay scale.
antiSMASHAlphaFoldClaude
1
Run assembled fungal genomes through antiSMASH (fungal mode) to catalog biosynthetic gene clusters — polyketides, nonribosomal peptides, terpenes — and prioritize novel or under-characterized clusters.
2
Use AlphaFold to predict structures of candidate enzymes or products and reason about function, then plan the wet-lab validation.
Copy-paste this prompt
I found a putative [nonribosomal peptide synthetase] biosynthetic gene cluster in a [Penicillium] genome via antiSMASH with low similarity to known clusters. Help me build a prioritization and validation plan: how to assess novelty, which bioinformatic evidence strengthens the case, how AlphaFold structure predictions could inform function, and the wet-lab steps (expression, extraction, bioassay) to confirm a real metabolite. Note where computational predictions are unreliable.
Genome mining and structure prediction generate hypotheses, not discoveries. Nothing is real until you culture, express, extract, and assay it in the lab.
3
Track candidates in a structured pipeline so promising clusters move to bench work and dead ends are documented.
What you'll haveA prioritized pipeline of discovery leads — the value proposition that gets a mycologist hired into drug or enzyme R&D.
3
Build a reliable AI-plus-DNA identification workflow
Why this pays: Accurate, fast identification underpins every applied contract — biocontrol, food safety, clinical mycology, biodiversity surveys. Combining computer-vision triage with confirmatory sequencing lets you handle high specimen volume without sacrificing the rigor clients require.
iNaturalistBLAST (NCBI)MycoMap
1
Use iNaturalist's vision model for rapid macrofungi triage in the field, treating it strictly as a hypothesis to be confirmed.
2
Confirm identity with sequence data and interpret the result correctly.
Copy-paste this prompt
I have an ITS sequence from an unknown fungal isolate and BLAST results against GenBank. Explain how to interpret this responsibly: what percent identity and query coverage actually support a species-level call for fungi, why GenBank contains misidentified reference sequences, when I must fall back to genus level, and when I should confirm against a curated database like UNITE or a type specimen. Give me a decision checklist.
Never make a species call from a top BLAST hit alone — GenBank is full of mislabeled sequences. Use curated references and expert review, especially for toxic or pathogenic taxa.
3
Log confirmed IDs and vouchers in MycoMap or your institution's collection so your calls are traceable and reusable.
What you'll haveHigh-throughput identification that still holds up scientifically — the reliability applied clients pay a premium for.
4
Accelerate literature synthesis and funded proposals
Why this pays: Whether in academia or industry, the mycologists who publish and win funding at a higher rate advance fastest. AI literature tools and proposal critique compress the slowest parts of the science, raising your output and your grant hit-rate.
ElicitConsensusClaude
1
Use Elicit to assemble structured evidence tables across the fungal literature and Consensus to map agreement and conflict — with links to the real papers.
2
Sharpen a proposal or manuscript with a large-context critique.
Copy-paste this prompt
Act as a skeptical grant reviewer for [applied/industrial mycology, e.g., a USDA or SBIR panel]. Here is my draft aims/summary on [mycoremediation of PFAS-contaminated soil]: [paste]. Identify the three weakest points (feasibility, novelty, commercial or ecological impact), tell me exactly how to strengthen each, and flag any claim needing a citation. Critique only — don't rewrite, and don't invent references.
Use AI to critique and organize, never to generate citations. Verify every reference against the actual paper before it enters a proposal.
What you'll haveMore proposals and papers at higher quality — the output rate that drives advancement and pay.
5
Move into the mycelium-materials and fermentation industry
Why this pays: Mycelium leather, packaging, and precision-fermentation companies are scaling fast and hiring scientists who can bridge biology and process. AI helps you translate lab mycology into the process, quality, and optimization language industry needs — the pivot into six-figure R&D roles.
ClaudeChatGPT (Code Interpreter)Python
1
Use ChatGPT's data-analysis mode or Python to analyze fermentation and growth data — substrate, temperature, humidity, yield — and model what drives performance.
2
Design experiments that optimize a bioprocess efficiently, in industry's terms.
Copy-paste this prompt
I'm optimizing solid-state cultivation of [a mycelium-materials fungus] on [agricultural waste substrate] for [material density and tensile strength]. Propose a design-of-experiments approach a lab scientist can run: which factors to vary (substrate mix, moisture, temperature, incubation time), a practical DOE design, the number of runs, and how to analyze the results statistically. Explain the tradeoffs versus one-factor-at-a-time.
AI can propose a design, but scale-up, contamination control, and safety are hands-on and organism-specific. Validate every parameter in your own lab.
3
Reframe your CV and portfolio around process, optimization, and reproducibility — the language mycelium-materials and fermentation employers hire on.
What you'll haveA demonstrated bridge from mycology to bioprocess — the profile that lands top-of-range industry R&D roles.
Your 12-month sequence to the top of the range
How the plays above stack into a path from median pay toward the $211,910 tier.
Month 1
Stand up an ITS metabarcoding pipeline (QIIME 2/DADA2 against UNITE) on one dataset with an AI coding assistant, using proper ITS settings and controls.
Months 2-3
Run available fungal genomes through antiSMASH and build a prioritized list of novel biosynthetic gene clusters worth bench validation.
Months 3-6
Tighten your ID workflow (vision triage plus confirmatory sequencing) and fold Elicit/Consensus into your writing to submit a paper or grant.
Months 6-12
Build an applied portfolio — bioprocess analysis or a discovery pipeline — and target biotech, agricultural-biologicals, or mycelium-materials roles.
Next steps for a Mycologist
Some links below are affiliate or partner links. PayCrunch may earn a commission if you enroll or subscribe through them, at no extra cost to you. Wage figures on this page still come from the Bureau of Labor Statistics, not from these programs.
Mycologist work is specific enough that a stamped 'check out these courses' block would be noise. BLS files this work as Biological Scientists, All Other (SOC 19-1029). O*NET Job Zone 5 is typical: graduate or professional school, so the honest next credential is a graduate-level or professional certificate — not a random catalog dump.
The occupation's listed knowledge area is Biology, which is what the course searches below actually query.
Mycologists in this dataset list Amazon Web Services AWS software among the tools in use, so a program that names that stack is a better fit than a survey course.
FlexJobs screens remote, hybrid, freelance, and flexible listings so you are not wading through unverified ads. This is a job-board search for Mycologist work, not a claim that they list a counted SOC 19-1029 inventory.
Write a Mycologist resume, or one aimed at Data Scientists, instead of a blank template. Resume Now is a resume builder; we are not claiming a counted template set for this SOC.
A Mycologist resume that names the actual tasks on this page, or the step-up title Data Scientists, beats a blank template when you apply.
What Mycologists earn by state
These are the Bureau of Labor Statistics’ own figures for Biological Scientists, All Other, state by state — not a cost-of-living adjustment applied to the national number. Only states employing at least 500 people in the occupation are shown, because a state median drawn from a handful of workers is noise rather than a signal.
Maryland
$121,680
highest of them · +23% vs the national median
Missouri
$63,290
lowest of the 28 states and D.C. that qualify · -36% vs the national median
The same job pays $58,390 more a year at the median in Maryland than in Missouri — 92% higher. That gap is what the Bureau measured, before any question of what it costs to live in either place. The top-of-range figure quoted at the head of this page, $211,910, is a different statistic in a different place: it is the 90th-percentile wage in District of Columbia. The state that pays the typical worker most and the state where the best-paid go highest are not always the same one.
Source: U.S. Bureau of Labor Statistics, Occupational Employment and Wage Statistics, May 2025, SOC 19-1022. 28 states and D.C. clear the 500-employee reporting floor for this occupation; those below it are left out rather than shown with a wide error band.
Free data. Use any of it.
PayCrunch publishes verified, BLS-sourced salary + AI-playbook data on 1,000+ professions — free, no signup.
No. AI can sort sequences and flag gene clusters, but the science is wet-lab: culturing fastidious fungi, running assays, microscopy, and confirming that a computational hit is a real, functional organism or molecule. AI can't do any of that, and it can't take responsibility for a toxin or pathogen call. It's augmentation — the mycologists who use it characterize communities and mine genomes far faster, which is exactly the applied output industry pays for.
Can I trust an AI or BLAST species identification?
Only as a hypothesis. iNaturalist vision IDs and top BLAST hits are frequently wrong for fungi because reference databases contain misidentified sequences and many taxa look alike. Confirm with curated references (UNITE), culture, and expert review — especially for toxic, edible, or pathogenic species where a wrong call has real consequences. The identification is your responsibility, not the tool's.
How does AI actually raise a mycologist's pay?
By unlocking applied, industry-facing work. Metabarcoding pipelines, genome mining for drug and enzyme leads, and bioprocess optimization are exactly what biotech, agricultural-biologicals, and mycelium-materials companies pay well for — and AI lets one scientist do them without a dedicated bioinformatics team. It moves you from taxonomy-scale pay toward industry R&D pay.
Is it safe to use AI to plan lab work with fungi?
Use it for drafts only. Fungi include pathogens and toxin producers, so biosafety level, containment, permits, and select-agent rules are set by your institution's biosafety officer and regulators — never by a chatbot. Treat any AI-generated protocol as a starting point to be reviewed and approved through proper channels before you touch an organism.
Which AI skill should I learn first?
Bioinformatics with an AI coding assistant. If you barcode fungi, start with an ITS metabarcoding pipeline against UNITE; if you have genome data, start with antiSMASH genome mining. Both convert data you already generate into the applied, fundable results that define a top-of-range mycology career.
Methodology & sources
Salary (median, 10th, top of the range) — U.S. Bureau of Labor Statistics, OEWS.
By state — the Bureau of Labor Statistics’ own state medians, limited to states employing at least 500 people in the occupation. No cost-of-living arithmetic is applied to a wage anywhere on this page.
The plays — PayCrunch's own step-by-step guidance using publicly available AI tools. Tool names/URLs are real and current as of August 2026; prompts written to work as-is. Verify any professional output before relying on it.