**An E-mail Interview with Jim Phillips at Boeing.**

Questions to Jim Phillips

These are questions that young mathematicians, some applied,

some pure, would like to ask someone in your position.

1. If you were beginning graduate school in mathematics today,

what courses would you take to be as valuable as possible

in the job market a few years from now?

I find this difficult to answer without talking about a complete

curriculum, and I'm not informed enough to lay such a thing out. A
Ph.D.

going into industry needs breadth (a good foundation that gives him/her
the

capacity to dig into a variety of areas of mathematics, and to "think

mathematically") and depth in SOME area. In general, most graduate
programs

provide both, between preparing students for qualifying or prelim exams,

and the Ph.D. work itself. Beyond that, one needs to develop an

understanding of where applied problems come from, and how one can
get a

grip on them and solve them. If you knew you were going into a particular

industry, it would be easier to say what to take to accomplish this.

Lacking that foresight, some solid courses in something like engineering

physics and mathematical modeling would be desirable. To learn more
about

common tools to use, a good numerical analysis foundation is a must.

Slightly (but not much) behind this, I would list optimization and

statistics. Since most physical based problems start with a PDE (or
at

least an ODE), some good background in those is most desirable. Finally,

some background in scientific computing issues (e.g., basics of data

structures, solving large scale problems on computers) is highly desirable.

I realize that even this basic list is a long one. One implication
of it is

that it is hard to take courses in a large number of these things if
your

primary interest area does not have a large overlap with them.

2. What are the mathematical tools that you use most?

What are the things I should be getting familiar with?

Is there a particular computer language or skill that

is absolutely necessary in a new hire?

In the environment my group is in at Boeing, numerical analysis is

probably the toolbag used most. I listed desirable "things to get familiar

with" in 1. above. There is no particular computer language or skill
that

is an "absolute" necessity. The overall requirement, however, is that
you

have experience using modern computing tools to solve non-trivial problems.

That might be done in different contexts, but the most common one today

(from my perspective) is a Unix environment, and experience with both
"C"

and Fortran. Someone with a reasonable computing background can generally

pick up other computing skills as needed.

3. Suppose you are talking to a brilliant, new math Ph.D. with a

"pure" background who really wants to get a job in industry

in the next year or so. What minimal re-education path

would you suggest?

Find a way to get involved in some real world problem solving, then
work

your tail off to fill in the background you need to solve the problems
at

hand. A post-doc at a national lab or industry would be one such

possibility. Another possibility if you are at or near a university:
start

spending time talking to colleagues in engineering or the sciences,
and get

involved (by volunteering, if necessary) in solving the mathematics-related

problems that come up in their research. While you are in limbo before

finding such a position, work you way through some good books or journals

that focus on engineering or physics applications, then develop computer

tools (mathematical models, algorithms, computer program) to re-solve
some

of the problems discussed there-in. Of course, if you are at a university,

you can also sit in on courses and seminars that are helpful, too.
But I

think the key thing is: Get involved in problem solving. Industrial

mathematics is neither a spectator sport nor one that you can experience
by

reading books or understanding more theoretical mathematics.

4. How many Ph.D.'s from mathematics are in your employ?

How many statisticians? Physicists?

PhDs: Math, 33; Statistics, 8; Physics, 2; Engineering, 6.

MS: 29 total.

5. How many hours per week does the average industrial mathematician

work?

40 is the standard expectation. Many work more, either because that
is

their professional style, or perhaps because they are carrying their
work

further on their own so they can get a paper or conference presentation

from it.

6. How is the work structured? Do they just hand you a project

and say, "This is your baby; get it done in 10 weeks?"

Or do you always work in a group? How big are these groups?

Is there always a deadline, or do some groups work on a

more open-ended timetable?

There is a great deal of variety here. I think that it is accurate to

say that most mathematicians in industry are part of groups dominated
by

folks with engineering or science backgrounds. As such, the mathematician

is part of a team working on a project of interest to their employer.
The

"mathematical part" is generally thoroughly entwined with the other
issues;

it cannot be easily separated. In particular, it is rare that the

mathematician will be handed a problem, sent off to solve it, and asked
to

bring back a solution on a platter. (When that does happen, the experienced

mathematician will immediately start asking questions, because he/she
will

immediately suspect that the problem they were asked to solve is not
the

REAL problem that needs solving.) A team working on any particular
problem

may vary from one to perhaps six or eight. There is often a hard deadline;

it depends on whether the problem under consideration is part of a
schedule

driven project (e.g., getting a new product to market by a target date),
or

whether it is part of longer term research and development. In the

environment I am in, the mathematicians often are working as consultants

around the company. Their customers may contract to have the mathematician

support them or their project at, say, a half-time level for a given
period

of weeks or months. Whether the support is continued beyond that depends
on

the state of the project and the need for further mathematical help
with

it.

7. How do you find the mathematicians you hire? Is there

a bulletin board where openings are posted?

Unfortunately, we have not been able to hire any for about 4 years due

to the recession in the industry. However, our usual sources of advertising

positions are ads in SIAM News, and announcements to e-mail distribution

lists such as NA-Net, a network of people interested in numerical analysis

issues. (Does the Young Mathematicians network list such openings in
your

newsletter?)

8. Suppose you are looking to hire an expert in P.D.E's and

after taking a look at the market and realizing you have

a hundred people to choose from, you start thinking about

what other attributes you want this person to have. What's

on that list?

Experience in, and a real interest in, solving real world problems.

Ability to interact with people and work in teams. Good communication

skills, both verbal and writing. Mathematical breadth, with depth in
the

PDE area (since that is what you hypothesize that I am looking for).
The

depth would include knowledge and experience in solving non-trivial
PDE

problems numerically, and a good understanding of some class of physical

problems (e.g., fluid dynamics or electromagnetics) that gives rise
to

PDEs.

9. If you could form your own applied science department to train

future employees, what would you put on the curriculum?

This gets back to question 1., or at least my answer to it. That is

really a tough question, because it is so tempting to list every

theoretical and applied area that one might use in his/her career.
But in

actuality, the details of what one takes formally are not as important
as

gaining the breadth overall, and depth in one area that I mentioned
before.

After that, the interest in, and experience with, solving real world

problems, and the attitude toward real world problem solving that one

brings to the job, outweigh specific curriculum requirements. Finally,
if I

were forming the department, the faculty hired would all recognize
that

their graduates can have interesting and fruitful careers in non-academic

settings, and that such careers are in no way second class or less

desirable than academic careers. They are simply a second career option.