One of the most significant decisions we face as scientists comes at the end of our
formal education. Choosing between industry and academia is easy for some, incredibly
fraught for others. The author has made two complete cycles between these career destinations,
including on the one hand 16 years in academia, as grad student (twice, in biology
and in computer science), post-doc, and faculty, and on the other hand 19 years in
two different industries (computer and pharmaceutical). The following rules reflect
that experience, and my own opinions.
Rule 1: Assess Your Qualifications
If you are a freshly minted Ph.D., you know that you will need a good post-doc or
two before you can be seriously considered for a junior faculty position. If you're
impatient, you might be thinking of industry as a way to short-circuit that long haul.
You should be aware that companies will strongly consider your post-doctoral experience
(or lack thereof) in determining your starting position and salary. While you may
not relish extending your indentured servitude in academia, any disadvantage, financial
and otherwise, can quickly be made up in the early years of your career in industry.
In other words, trying to get off the mark quickly is not necessarily a good reason
to choose industry over academia.
On the other hand, you may have completed an undergraduate or Master's program with
a view to going to industry all along, with never a thought of an academic career.
You should still consider the point of the previous paragraph. While abbreviated “practical”
bioinformatics training programs can be excellent, a Ph.D. is a significant advantage
in all but the most IT-oriented positions in industry, at least at the outset. This
is not to discourage anyone from embarking on a fast-track-to-industry program if
their heart is in it, but be aware that the further you climb the educational ladder,
the higher and faster you can start when you step across to the business ladder, and
the better you will compete for a job in the first place. The days are long past when
bioinformaticists were in such short supply that any qualification would do.
If you are an old hand and have already notched up a post-doc or two, take stock of
your star power. This unspoken but universally understood metric encompasses such
factors as whom you've trained with, where you've published (and how much), and what
recent results of yours are on everyone's lips. If you are fortunate enough to have
significant capital in this department, then the world may be your oyster, but you
still need to consider where you will get the greatest leverage. While your stardom
may be less taken for granted in industry, my feeling is that academia is a better
near-term choice in such circumstances. Consider that it was in academia that you
achieved the success you own thus far, so you obviously “get it.” The simple fact
is that academia is rather more of a star system (as in Hollywood) than is industry.
Finally, if you count among your qualifications a stint in industry already, as an
intern or perhaps as part of a collaboration, you will not only be in a better position
to compete for a permanent job, but you will be much better prepared to make the decision
facing you. Stated another way, if you are seriously considering industry as a career
path, you should probably have already taken advantage of the many opportunities out
there to dip your toes in the water.
Rule 2: Assess Your Needs
In taking stock of your needs, and perhaps those of your family, a decent living is
generally at or near the top of the list. Salaries are still higher in industry, though
the gap is not nearly so wide as it once was. If you need a quick infusion of cash,
companies may offer signing bonuses, though again these were more common when bioinformatics
was a rarer commodity.
Industry offers forms of compensation unavailable in academia, and you will need to
consider how to value them relative to your present and future needs. Despite recent
bad press, bonus systems are often part of the equation, and depending on your entry
point they may constitute a significant percentage of total compensation. There is
a tendency among academics to discount bonus programs in their comparison shopping,
sometimes to zero, and this is a mistake. Bonuses are considered core aspects of compensation
in most companies, and though they always have a performance-based multiplier, the
base levels have historically been fairly dependable. That said, these are tough times
in industry, and there are no guarantees. Your best strategy is to understand the
reward system thoroughly, ask for historical data, and avoid comparing only base salaries
unless you are extraordinarily risk-averse.
Share options are another matter. While in the past these were very attractive, and
fruitful in practice, most industry types will tell you frankly that any options they've
received in the past decade are deep underwater and a deep disappointment. Many consider
pharma shares (and therefore options) to be a bargain at the moment, but that's between
you and your financial adviser to assess. In any case, it is not a short-term consideration,
since options typically take several years to vest.
If you are looking at biotech, however, share options and similar ownership schemes
need to be a key consideration, since these are a major rationale for assuming risk—more
on that below.
Finally, you may have more specific needs to consider, such as a spouse also in need
of a job. The two-body problem has always been tougher in academia than in industry,
and probably always will be. If you are both academics, note that industry often has
good contacts with local universities, and can facilitate interviews. Being a star
certainly helps, so don't be afraid to negotiate. In fact, a general rule of thumb
is that it never hurts to make your specific needs known, within reason. Academia
will try to accommodate them as a community, while on the other hand business (particularly
large, diversified companies) may have resources to address them that you wouldn't
have expected. Nobody wants to hear a peremptory demand, but if a company wants you,
be sure to let them know anything that might offer them a way to attract you.
Rule 3: Assess Your Desires
There are needs, and then there are desires. Do you want riches? Fame? A life at the
frontiers of knowledge? The hurly-burly of the business world? How do you really feel
about teaching, publishing, managing, interacting, traveling, negotiating, collaborating,
presenting, reporting, reviewing, fundraising, deal-making, and on and on? Though
it may seem obvious, this is a good time to decide what really drives you.
First, the obvious. Do you want to teach? If lecturing is in your blood, your decision
is made, although if a smattering will suffice you may have the option from within
industry of an adjunct academic appointment. (By the same token, if you are not so
enchanted with lecturing, grading, tutoring, etc., there are often options for research
track professorships that minimize teaching duties.) Do you want to publish? While
it will always be “publish or perish” in academia, it is certainly possible to grow
your CV in industry, and it can even enhance your career, depending on the company.
However, it might be largely on your own time, and you will likely encounter restrictions
in proprietary matters, though in practice you can generally find ways to work within
them. Ask about publication at the interview, both policies and attitudes, and watch
out for any defensiveness.
An important question, surprisingly often overlooked, is how you want to actually
spend your time, day by day and hour by hour. In academia, you will immediately be
plunged into hands-on science, and your drivers will be to start out on your career
by getting results, publishing, networking, and building your reputation with a view
to impressing your tenure committee. A career in industry may put more of an early
emphasis on your organizational aptitude, people skills, powers of persuasion, ability
to strategize and execute to plan, etc.; in terms of growing your reputation, your
audience will be the rather narrower community of your immediate management. A somewhat
more cynical view would be that in business you will spend seemingly endless hours
in meetings and writing plans and reports, while in academia you will spend all that
time and more in grantsmanship—in this regard, you must pick your poison.
Finally there is the elephant-in-the-room question: Do you want to make money, or
to help people? This is, of course, a false dichotomy, but many people consciously
or unconsciously frame the decision in just this way, and you had best deal with it.
Try thinking of it not so much in terms of the profit motives of the respective institutions,
but in terms of the people with whom you would spend your career. You should have
encountered a good sampling of scientists from industry during meetings, internships,
collaborations, interviews, etc. (or in any case you should certainly try to do so
before making judgments). If you are left in any doubt as to their ethics or sincere
desire to relieve human suffering as efficiently as possible, or if you feel these
are somehow trumped by the corporate milieu, then by all means choose academia—but
only after applying analogous tests to the academics you already know well. In my
experience, business doesn't have a monopoly on greed, nor are humanitarian impulses
restricted to academia. That said, in the final analysis you must be comfortable with
your role in the social order and not finesse the question.
Rule 4: Assess Your Personality
Not surprisingly, some personality types are better-suited to one environment or the
other. Raw ambition can be viewed as unseemly in either case, but there is more latitude
for it in industry, and greater likelihood of being recognized and rewarded sooner
if you are “on the go.” In fact, one of the clearest differences between academia
and industry are their respective time constants. Although the pace of academia may
have quickened of late, it is still stately by comparison with industry, and much
more scheduled (so many years to tenure, so many months to a funding decision, etc.).
If you are impatient, industry offers relatively fast-paced decision-making and constant
change. If you thrive more under structured expectations, academia would be better
for you, for although industry has all the trappings of long-range strategies and
career planning, the highly reactive environment means these are more honored in the
breach. For one thing, reorganizations are common, and in the extreme case mergers
(I have experienced two) can reset everything, for good or ill, and devour many months.
This is not to say that all is chaos—industry certainly favors a goal-directed personality,
but with plenty of flexibility. On the other hand, flexibility is more the hallmark
of academic research, where you will have the opportunity to follow wherever the science
leads, once you are running your own shop. In industry, the flexibility is more of
the conforming sort, since you won't be able to investigate every promising lead and
change your research direction at will. In academia, diverging from the Specific Aims
of a grant may be a problem when the time comes to renew, but the risk is yours, as
is the reward. In industry, you can make the case for a new program of research, but
the decision is management's and will be guided by business considerations. The “lone
wolf” or “one-person band” may be increasingly rare in academia in an age of collaboration,
but it is unheard of in industry, where being able to work in teams with specialized
division of labor is essential. It should be apparent, as well, that mavericks and
quirky personalities tend to do better in academia.
The pecking order in industry is deeper and more pyramidal than in academia, and you
might end up languishing in a pay grade (or feel like you are), but there are usually
plenty of opportunities for lateral moves and a variety of experiences—not to mention
that it's easier to switch companies than colleges. In industry, one does need to
be able to thrive in a hierarchy; you will always answer to someone, though the degree
to which you are monitored will vary. By the same token, if your personality is such
that climbing a management ladder and assuming steadily greater responsibility suits
you, industry is built for that, and plenty of management training is on offer in
larger companies. Learning to manage is much more hit-or-miss in academia; opportunities
to lead large organizations are rare (and to manage them actively rather than by consensus,
rarer still).
If your personality type is that of a risk-taker, biotechs and/or startups may fit
you to a tee. These are the wild and wooly end of the industry spectrum, and the risks
and rewards are well-known. You will work longer hours than in large pharma, and maybe
even more than in academia. You will most likely share more in ownership, and learn
entrepreneurial skills that will serve you well, once the bug has bitten. Bear in
mind the very common pattern of faculty spinning off startups or otherwise participating
in boards and the like, not to mention staking out intellectual property (shared with
their university); thus, you may well be able to scratch this itch from the vantage
of academia as well.
A final word about politics. Whether you are an enthusiastically political animal,
or abhor this aspect of the human condition, you will encounter plenty of politics
in both academia and industry. The flavors differ, to be sure. As a student you doubtless
heard the clichés about tedious academic committees and underhanded deans, but you
have probably had more exposure to the realities behind those stories than the corresponding
ones about the dog-eat-dog corporate world. Company politics, I would hazard to say,
are more transparent—the maneuvering more open and the motives more apparent. The
results are often more life-altering, unbuffered by tenure and academic convention.
Again, it is a matter of taste, but in my opinion the differences are overblown, for
the simple reason that people are the same everywhere, in both environments governed
by an underlying sense of fair play, but also occasional opportunism.
Rule 5: Consider the Alternatives
As I've suggested, the choice you face is far more fine-grained than simply that between
industry and academia. Industry is a spectrum, from large pharma to mature biotech
to startup. By the same token, the academic side has at one extreme the research powerhouses,
where you will be judged by volume of grants, and at the other the teaching institutions,
which may not even have graduate departments. Unless you are very sure of yourself,
you'd be well-advised to consider the full range, given the competition you may face.
Also, don't neglect other careers that may value your training. If you love the language,
consider science journalism, either writing or editing—Science and Nature have large
staffs, and you will often encounter them and representatives of other journals at
the same scientific meetings you attend. The same is true of government agencies such
as the NIH, NSA, DOE, and so forth, where grants administration is very actively tied
to research trends and can be an entrée into the world of science policy. There are
many more such positions when foundations, interest groups, and other private funding
bodies are included. If you have a knack for business, many management consulting
firms have scientific and technical consulting arms that value Ph.D.s and offer intensive
training opportunities, and, though it may not be attractive at the moment, a career
as a financial analyst specializing in biotech is yet another possibility.
Rule 6: Consider the Timing
The current business environment cannot help but be among your considerations. Pharma
has certainly been contributing to the unemployment rolls of late. Corporate strategies,
which used to be very similar across the sector, have started to diverge, so that
some companies are divesting bioinformatics at the same time that others are hiring
computational types disproportionately as they place more of an emphasis on mathematical
modeling, systems approaches, pharmacogenomics, drug repurposing, and the like. Overall,
though, the industry trend has been to shrink R&D, and this may well continue through
a round of consolidation, with several mega-mergers now under way. As noted above,
mergers are times of upheaval, carrying both risk and opportunity, and usually a period
in limbo as well. At the same time, it is worth bearing in mind that a corollary of
downsizing is outsourcing, so that there may be new opportunities for startups and
even individual consultants.
For much of the last decade, academia has also been in the doldrums, as NIH budgets
have effectively contracted. As I write this, things are definitely looking up, with
prospects for renewed funding of science and even near-term benefits to the NIH and
NSA from the Obama stimulus package. Whether universities will respond proportionately
with faculty hiring, given the losses in their endowment funds and cutbacks in salaries
and discretionary spending, remains to be seen. There is a lot of slack to be taken
up, and in particular a backlog of meritorious grant applications that are now being
reconsidered. Nevertheless, on balance, an academic career has to be somewhat more
promising today than a year ago, and a career in pharma rather less so, in the opinion
of the author.
Rule 7: Plan for the Long Term
Having noted the current situation in Rule 6, it's important also to say that a career
decision should be made with the long haul in mind. The business cycle will eventually
reverse itself, and while the business model may need to change irrevocably, the aging
population alone dictates that healthcare will be an increasing global priority. Likewise,
history shows that growth in government funding for science waxes and wanes, with
a time constant somewhat longer than a decade. Trying to optimize a career decision
based on current conditions is a bit like trying to time the stock market—you are
sure to be overtaken by events.
One approach is to choose some reasonably long time frame, perhaps a decade, and ask
yourself whether you'd be content to have lived through the average ups and downs
you'd experience in a given job over that period. In academia, that would include
a tenure decision (rate your chances), a lot of grant applications with mixed success
at best, and maybe some great students and really significant scientific contributions.
In pharma or large biotech, it would encompass a couple of promotions, your own group
and maybe a department, at least one merger or other big disruption, and several rounds
of layoffs. In small business, it might include a failed startup (or two, or three),
an IPO if you're lucky, and a lucrative exit strategy or long-term growth if you're
really lucky.
If you game these scenarios with various probabilities, and use your imagination,
it just might become clear which ones you have no stomach for, and which ones really
hold your interest.
Rule 8: Keep Your Options Open
Job-hopping is much more prevalent now than in days of yore, and you should consider
this in your scenarios. In industry, there is little stigma attached to changing employers,
and if you can tolerate the relocation and/or want to see the world, it is a more
or less standard way to advance your career by larger-than-usual increments. This
stratagem is far from unknown in academia, but perhaps a bit trickier to execute,
though of course it is de rigueur if you fail to get tenure.
Of greater interest is the question of moving between academia and industry. From
the former to the latter is fairly easy, but the reverse is not as common, for a variety
of reasons. Superstar academics in relevant areas are in great demand in industry,
to which they are often exposed through consulting or scientific advisory boards.
There are multiple examples of senior academics taking over major R&D organizations
in industry, sometimes orders of magnitude larger than anything they managed in academia,
and you might even consider this well-trod path as a career goal from the outset.
It is not impossible to return to academia from industry, particularly if you were
already quite prominent when you left, but if you start your career in industry you
may be at a disadvantage unless you go to great lengths to maintain an academic-style
publication record and CV. Important exceptions would be if the work that you did
in industry was particularly novel and/or high-profile, or if your business experience
is valued in the post you seek. Examples of the latter might be faculty positions
with a prominent management component (centers, institutes, core facilities, and the
like), or an interface role back to industry, or perhaps a joint business school appointment.
Rule 9: Be Analytic
Approach the decision with the analytic skills you've learned to apply to scientific
questions. Gather data from all available sources and organize it systematically.
When you interview, don't just impress, but get impressions; record everything down
to your gut feelings. Do some bibliometric or even social network analyses of your
potential colleagues. Check the industry newsletters and blogs, albeit with a grain
of salt, to get a sense of the mood around R&D units (not to be confused with manufacturing,
sales and marketing, or other divisions, which may have completely different cultures
within the same company).
You might even try out some decision theoretic methodologies, such as decision matrices
and Bayesian decision trees, or run simulations on the scenarios of Rule 7. I recommend
taking a look at expected utility theory and prospect theory, for an interesting quantitative
excursion. But honestly, these suggestions are just a more sophisticated informatics
version of the classic advice to “make a list of pros and cons,” which always makes
one feel a little more in control.
Rule 10: Be Honest with Yourself
Another homily: Now, if ever, is the time to be honest with yourself. Take a hard
look at your qualifications, with as much objectivity as you can muster, and use these
rules to decide where you would be best-suited and positioned for success. But even
more importantly, deal with your emotional responses to industry and academia. If
something is nagging at you, tease it out into the open, and try to decide if it is
well-founded or not; if you can't decide, then you have to acknowledge it, and realize
that it may not go away in the future either.
Finally, try to keep some perspective. Your career choice is important, but not irrevocable,
and there are more consequential things in life. Don't let the decision process ruin
what should be an exciting time for you.