model {
for (i in 1:5) {
y[i] ~ dnorm(mu[i], tau)
mu[i] <- alpha + beta*(x[i] - mean(x[]))
}
alpha ~ dflat()
beta ~ dflat()
tau <- 1/sigma2
log(sigma2) <- 2*log.sigma
log.sigma ~ dflat()
}

Data:
list(y = c(177,236,285,350,376), x = c(8,15,22,29,36))

Inits:
list(alpha=250,beta=0,log.sigma=0)

   node   mean   sd   MC error   2.5%   median   97.5%   start   sample
   alpha   284.8   7.89   0.078   269.9   284.8   300.1   4001   10000
   beta   7.316   0.7814   0.008582   5.82   7.316   8.819   4001   10000
   sigma2   316.3   743.6   26.14   37.24   145.6   1586.0   4001   10000